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liu-soo-1994-corpus
https://aclanthology.org/C94-1073
A Corpus-Based Learning Technique for Building A Self-Extensible Parser
IIuman intervention and/or training corpora tagged with various kinds of information were often assumed in many natural language acquisition models. This assumption is a major source of inconsistencies, errors, and inefficiency in learning. In this paper, we explore the extent to which a parser may extend itself withou...
false
[]
[]
null
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null
Acknowledgement This research is supported in part by NSC (National Science Council of R.@.C.) under the grant NSC83-0408-E-007-008.
1994
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ikehara-etal-1996-statistical
https://aclanthology.org/C96-1097
A Statistical Method for Extracting Uninterrupted and Interrupted Collocations from Very Large Corpora
In order to extract rigid expressions with a high frequency of use, new algorithm that can efficiently extract both uninterrupted and interrupted collocations from very large corpora has been proposed. The statistical method recently proposed for calculating N-gram of m'bitrary N can be applied to the extraction of uni...
false
[]
[]
null
null
null
null
1996
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ren-etal-2020-simulspeech
https://aclanthology.org/2020.acl-main.350
SimulSpeech: End-to-End Simultaneous Speech to Text Translation
In this work, we develop SimulSpeech, an endto-end simultaneous speech to text translation system which translates speech in source language to text in target language concurrently. SimulSpeech consists of a speech encoder, a speech segmenter and a text decoder, where 1) the segmenter builds upon the encoder and levera...
false
[]
[]
null
null
null
This work was supported in part by the National Key R&D Program of China (Grant No.2018AAA0100603), Zhejiang Natural Science Foundation (LR19F020006), National Natural Science Foundation of China (Grant No.61836002), National Natural Science Foundation of China (Grant No.U1611461), and National Natural Science Foundati...
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
tam-etal-2019-optimal
https://aclanthology.org/P19-1592
Optimal Transport-based Alignment of Learned Character Representations for String Similarity
String similarity models are vital for record linkage, entity resolution, and search. In this work, we present STANCE-a learned model for computing the similarity of two strings. Our approach encodes the characters of each string, aligns the encodings using Sinkhorn Iteration (alignment is posed as an instance of optim...
false
[]
[]
null
null
null
1 We used a xml dump of Wikipedia from 2016-03-05. We restrict the entities and hyperlinked spans to come from non-talk, non-list Wikipedia pages.
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
mundra-etal-2021-wassa
https://aclanthology.org/2021.wassa-1.12
WASSA@IITK at WASSA 2021: Multi-task Learning and Transformer Finetuning for Emotion Classification and Empathy Prediction
This paper describes our contribution to the WASSA 2021 shared task on Empathy Prediction and Emotion Classification. The broad goal of this task was to model an empathy score, a distress score and the overall level of emotion of an essay written in response to a newspaper article associated with harm to someone. We ha...
true
[]
[]
Good Health and Well-Being
null
null
null
2021
false
false
true
false
false
false
false
false
false
false
false
false
false
false
false
false
false
light-1996-morphological
https://aclanthology.org/P96-1004
Morphological Cues for Lexical Semantics
Most natural language processing tasks require lexical semantic information. Automated acquisition of this information would thus increase the robustness and portability of NLP systems. This paper describes an acquisition method which makes use of fixed correspondences between derivational affixes and lexical semantic ...
false
[]
[]
null
null
null
A portion of this work was performed at the University of Rochester Computer Science Department and supported by ONR/ARPA research grant number N00014-92-J-1512.
1996
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
janssen-2021-udwiki
https://aclanthology.org/2021.udw-1.7
UDWiki: guided creation and exploitation of UD treebanks
UDWiki is an online environment designed to make creating new UD treebanks easier. It helps in setting up all the necessary data needed for a new treebank up in a GUI, where the interface takes care of guiding you through all the descriptive files needed, adding new texts to your corpus, and helping in annotating the t...
false
[]
[]
null
null
null
null
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
bod-2007-linguistic
https://aclanthology.org/W07-0601
A Linguistic Investigation into Unsupervised DOP
Unsupervised Data-Oriented Parsing models (U-DOP) represent a class of structure bootstrapping models that have achieved some of the best unsupervised parsing results in the literature. While U-DOP was originally proposed as an engineering approach to language learning (Bod 2005, 2006a), it turns out that the model has...
false
[]
[]
null
null
null
null
2007
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
indurkhya-2021-using
https://aclanthology.org/2021.ranlp-1.71
Using Collaborative Filtering to Model Argument Selection
This study evaluates whether model-based Collaborative Filtering (CF) algorithms, which have been extensively studied and widely used to build recommender systems, can be used to predict which common nouns a predicate can take as its complement. We find that, when trained on verb-noun co-occurrence data drawn from the ...
false
[]
[]
null
null
null
Three anonymous reviewers are thanked for critically reading the manuscript and providing helpful comments.
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
claeser-etal-2018-multilingual
https://aclanthology.org/W18-3218
Multilingual Named Entity Recognition on Spanish-English Code-switched Tweets using Support Vector Machines
This paper describes our system submission for the ACL 2018 shared task on named entity recognition (NER) in codeswitched Twitter data. Our best result (F1 = 53.65) was obtained using a Support Vector Machine (SVM) with 14 features combined with rule-based postprocessing.
false
[]
[]
null
null
null
null
2018
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
blackwood-etal-2010-fluency
https://aclanthology.org/C10-1009
Fluency Constraints for Minimum Bayes-Risk Decoding of Statistical Machine Translation Lattices
A novel and robust approach to improving statistical machine translation fluency is developed within a minimum Bayesrisk decoding framework. By segmenting translation lattices according to confidence measures over the maximum likelihood translation hypothesis we are able to focus on regions with potential translation e...
false
[]
[]
null
null
null
We would like to thank Matt Gibson and the human judges who participated in the evaluation. This work was supported in part under the GALE program of the Defense Advanced Research Projects Agency, Contract No. HR0011-06-C-0022 and the European Union Seventh Framework Programme (FP7-ICT-2009-4) under Grant Agreement No....
2010
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ikehara-etal-1991-toward
https://aclanthology.org/1991.mtsummit-papers.16
Toward an MT System without Pre-Editing: Effects of a New Method in ALT-J/E
Recently, several types of Japanese to English MT (machine translation) systems have been developed, but prior to using such systems, they have required a pre-editing process of rewriting the original text into Japanese that could be easily translated. For communication of translated information requiring speed in diss...
false
[]
[]
null
null
null
The authors wish to thank Dr. Masahiro Miyazaki, Mr. Kentarou Ogura and other members of the research group on MT for their valuable contribution to discussions.
1991
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
chalaguine-schulz-2017-assessing
https://aclanthology.org/E17-4008
Assessing Convincingness of Arguments in Online Debates with Limited Number of Features
We propose a new method in the field of argument analysis in social media to determining convincingness of arguments in online debates, following previous research by Habernal and Gurevych (2016). Rather than using argument specific feature values, we measure feature values relative to the average value in the debate, ...
false
[]
[]
null
null
null
We thank our colleague Oana Cocarascu from Imperial College London who provided insight and expertise that greatly assisted the research, as well as Luka Milic for assistance with the implementation of the neural network.
2017
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
pezzelle-etal-2018-comparatives
https://aclanthology.org/N18-1039
Comparatives, Quantifiers, Proportions: a Multi-Task Model for the Learning of Quantities from Vision
The present work investigates whether different quantification mechanisms (set comparison, vague quantification, and proportional estimation) can be jointly learned from visual scenes by a multi-task computational model. The motivation is that, in humans, these processes underlie the same cognitive, nonsymbolic ability...
false
[]
[]
null
null
null
We kindly acknowledge Gemma Boleda and the AMORE team (UPF), Raquel Fernández and the Dialogue Modelling Group (UvA) for the feedback, advice and support. We are also grateful to Aurélie Herbelot, Stephan Lee, Manuela Piazza, Sebastian Ruder, and the anonymous reviewers for their valuable comments. This project has rec...
2018
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
hsieh-etal-2019-robustness
https://aclanthology.org/P19-1147
On the Robustness of Self-Attentive Models
This work examines the robustness of selfattentive neural networks against adversarial input perturbations. Specifically, we investigate the attention and feature extraction mechanisms of state-of-the-art recurrent neural networks and self-attentive architectures for sentiment analysis, entailment and machine translati...
false
[]
[]
null
null
null
We are grateful for the insightful comments from anonymous reviewers. This work is supported by the Ministry of Science and Technology of Taiwan under grant numbers 107-2917-I-004-001, 108-2634-F-001-005. The author Yu-Lun Hsieh wishes to acknowledge, with thanks, the Taiwan International Graduate Program (TIGP) of Aca...
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
hahn-choi-2019-self
https://aclanthology.org/R19-1050
Self-Knowledge Distillation in Natural Language Processing
Since deep learning became a key player in natural language processing (NLP), many deep learning models have been showing remarkable performances in a variety of NLP tasks, and in some cases, they are even outperforming humans. Such high performance can be explained by efficient knowledge representation of deep learnin...
false
[]
[]
null
null
null
null
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
vanni-zajac-1996-temple
https://aclanthology.org/X96-1024
The Temple Translator's Workstation Project
Tipster document management architecture and it allows both translator/analysts and monolingual analysts to use the machinetranslation function for assessing the relevance of a translated document or otherwise using its information in the performance of other types of information processing. Translators can also use it...
false
[]
[]
null
null
null
null
1996
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
tihelka-matousek-2004-design
http://www.lrec-conf.org/proceedings/lrec2004/pdf/119.pdf
The Design of Czech Language Formal Listening Tests for the Evaluation of TTS Systems
This paper presents an attempt to design listening tests for the Czech synthesis speech evaluation. The design is based on standardized and widely used listening tests for English; therefore, we can benefit from the advantages provided by standards. Bearing the Czech language phenomena in mind, we filled the standard f...
false
[]
[]
null
null
null
null
2004
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
lin-dyer-2009-data
https://aclanthology.org/N09-4001
Data Intensive Text Processing with MapReduce
This half-day tutorial introduces participants to data-intensive text processing with the MapReduce programming model [1], using the open-source Hadoop implementation. The focus will be on scalability and the tradeoffs associated with distributed processing of large datasets. Content will include general discussions ab...
false
[]
[]
null
null
null
This work is supported by NSF under awards IIS-0705832 and IIS-0836560; the Intramural Research Program of the NIH, National Library of Medicine; DARPA/IPTO Contract No. HR0011-06-2-0001 under the GALE program. Any opinions, findings, conclusions, or recommendations expressed here are the instructors' and do not necess...
2009
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
vulic-korhonen-2016-role
https://aclanthology.org/P16-1024
On the Role of Seed Lexicons in Learning Bilingual Word Embeddings
A shared bilingual word embedding space (SBWES) is an indispensable resource in a variety of cross-language NLP and IR tasks. A common approach to the SB-WES induction is to learn a mapping function between monolingual semantic spaces, where the mapping critically relies on a seed word lexicon used in the learning proc...
false
[]
[]
null
null
null
This work is supported by ERC Consolidator Grant LEXICAL: Lexical Acquisition Across Languages (no 648909). The authors are grateful to Roi Reichart and the anonymous reviewers for their helpful comments and suggestions.
2016
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
li-etal-2021-tdeer
https://aclanthology.org/2021.emnlp-main.635
TDEER: An Efficient Translating Decoding Schema for Joint Extraction of Entities and Relations
Joint extraction of entities and relations from unstructured texts to form factual triples is a fundamental task of constructing a Knowledge Base (KB). A common method is to decode triples by predicting entity pairs to obtain the corresponding relation. However, it is still challenging to handle this task efficiently, ...
false
[]
[]
null
null
null
null
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
schilder-1999-reference
https://aclanthology.org/W99-0112
Reference Hashed
This paper argues for a novel data structure for the representation of discourse referents. A so-called hashing list is employed to store discourse referents according to their grammatical features. The account proposed combines insights from several theodes of discourse comprehension. Segmented Discourse Representatio...
false
[]
[]
null
null
null
I would like to thank the two annomynous reviewers to their comments and feedback. Special thanks to Christie Manning for providing me with all her help.
1999
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
mosbach-etal-2020-interplay
https://aclanthology.org/2020.blackboxnlp-1.7
On the Interplay Between Fine-tuning and Sentence-Level Probing for Linguistic Knowledge in Pre-Trained Transformers
Fine-tuning pre-trained contextualized embedding models has become an integral part of the NLP pipeline. At the same time, probing has emerged as a way to investigate the linguistic knowledge captured by pre-trained models. Very little is, however, understood about how fine-tuning affects the representations of pre-tra...
false
[]
[]
null
null
null
We thank Badr Abdullah for his comments and suggestions. We would also like to thank the reviewers for their useful comments and feedback, in particular R1. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) -project-id 232722074 -SFB 1102.
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
kundu-choudhury-2014-know
https://aclanthology.org/W14-5127
How to Know the Best Machine Translation System in Advance before Translating a Sentence?
The aim of the paper is to identify a machine translation (MT) system from a set of multiple MT systems in advance, capable of producing most appropriate translation for a source sentence. The prediction is done based on the analysis of a source sentence before translating it using these MT systems. This selection proc...
false
[]
[]
null
null
null
null
2014
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ravi-kozareva-2019-device
https://aclanthology.org/P19-1368
On-device Structured and Context Partitioned Projection Networks
A challenging problem in on-device text classification is to build highly accurate neural models that can fit in small memory footprint and have low latency. To address this challenge, we propose an on-device neural network SGNN++ which dynamically learns compact projection vectors from raw text using structured and co...
false
[]
[]
null
null
null
We would like to thank the organizers of the customer feedback challenging for sharing the data and the anonymous reviewers for their valuable feedback and suggestions.
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
etcheverry-wonsever-2019-unraveling
https://aclanthology.org/P19-1319
Unraveling Antonym's Word Vectors through a Siamese-like Network
Discriminating antonyms and synonyms is an important NLP task that has the difficulty that both, antonyms and synonyms, contains similar distributional information. Consequently, pairs of antonyms and synonyms may have similar word vectors. We present an approach to unravel antonymy and synonymy from word vectors based...
false
[]
[]
null
null
null
null
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
slawik-etal-2015-stripping
https://aclanthology.org/2015.eamt-1.18
Stripping Adjectives: Integration Techniques for Selective Stemming in SMT Systems
In this paper we present an approach to reduce data sparsity problems when translating from morphologically rich languages into less inflected languages by selectively stemming certain word types. We develop and compare three different integration strategies: replacing words with their stemmed form, combined input usin...
false
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[]
null
null
null
The project leading to this application has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement n • 645452.
2015
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
di-eugenio-1992-understanding
https://aclanthology.org/P92-1016
Understanding Natural Language Instructions: The Case of Purpose Clauses
This paper presents an analysis of purpose clauses in the context of instruction understanding. Such analysis shows that goals affect the interpretation and / or execution of actions, lends support to the proposal of using generation and enablement to model relations between actions, and sheds light on some inference p...
false
[]
[]
null
null
null
For financial support I acknowledge DARPA grant no. N0014-90-J-1863 and ARt grant no. DAALO3-89-C0031PR1. Thanks to Bonnie Webber for support, insights and countless discussions, and to all the members of the AnimNL group, in particular to Mike White. Finally, thanks to the Dipartimento di Informatica -Universita' di T...
1992
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
piits-etal-2007-designing
https://aclanthology.org/W07-2459
Designing a Speech Corpus for Estonian Unit Selection Synthesis
The article reports the development of a speech corpus for Estonian text-to-speech synthesis based on unit selection. Introduced are the principles of the corpus as well as the procedure of its creation, from text compilation to corpus analysis and text recording. Also described are the choices made in the process of p...
false
[]
[]
null
null
null
The support from the program Language Technology Support of the Estonian has made the present work possible.
2007
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
choi-etal-2010-propbank
http://www.lrec-conf.org/proceedings/lrec2010/pdf/73_Paper.pdf
Propbank Frameset Annotation Guidelines Using a Dedicated Editor, Cornerstone
This paper gives guidelines of how to create and update Propbank frameset files using a dedicated editor, Cornerstone. Propbank is a corpus in which the arguments of each verb predicate are annotated with their semantic roles in relation to the predicate. Propbank annotation also requires the choice of a sense ID for e...
false
[]
[]
null
null
null
We gratefully acknowledge the support of the National Science Foundation Grants CISE-CRI-0551615, Towards a Comprehensive Linguistic Annotation and CISE-CRI 0709167, Collaborative: A Multi-Representational and Multi-Layered Treebank for Hindi/Urdu, and a grant from the Defense Advanced Research Projects Agency (DARPA/I...
2010
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ueda-washio-2021-relationship
https://aclanthology.org/2021.acl-srw.6
On the Relationship between Zipf's Law of Abbreviation and Interfering Noise in Emergent Languages
This paper studies whether emergent languages in a signaling game follow Zipf's law of abbreviation (ZLA), especially when the communication ability of agents is limited because of interfering noises. ZLA is a wellknown tendency in human languages where the more frequently a word is used, the shorter it will be. Surpri...
false
[]
[]
null
null
null
We would like to thank Professor Yusuke Miyao for supervising our research, Jason Naradowsky for fruitful discussions and proofreading, and the anonymous reviewers for helpful suggestions. The first author would also like to thank his colleagues Taiga Ishii and Hiroaki Mizuno as they have encouraged each other in their...
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
indig-etal-2018-whats
https://aclanthology.org/L18-1091
What's Wrong, Python? -- A Visual Differ and Graph Library for NLP in Python
The correct analysis of the output of a program based on supervised learning is inevitable in order to be able to identify the errors it produced and characterise its error types. This task is fairly difficult without a proper tool, especially if one works with complex data structures such as parse trees or sentence al...
false
[]
[]
null
null
null
null
2018
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
brandt-skelbye-dannells-2021-ocr
https://aclanthology.org/2021.ranlp-1.23
OCR Processing of Swedish Historical Newspapers Using Deep Hybrid CNN--LSTM Networks
Deep CNN-LSTM hybrid neural networks have proven to improve the accuracy of Optical Character Recognition (OCR) models for different languages. In this paper we examine to what extent these networks improve the OCR accuracy rates on Swedish historical newspapers. By experimenting with the open source OCR engine Calamar...
false
[]
[]
null
null
null
This work has been funded by the Swedish Research Council as part of the project Evaluation and refinement of an enhanced OCR-process for mass digitisation (2019-2020; dnr IN18-0940:1). It is also supported by Språkbanken Text and Swe-Clarin, a Swedish consortium in Common Language Resources and Technology Infrastructu...
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
amin-etal-2022-using
https://aclanthology.org/2022.ltedi-1.5
Using BERT Embeddings to Model Word Importance in Conversational Transcripts for Deaf and Hard of Hearing Users
Deaf and hard of hearing individuals regularly rely on captioning while watching live TV. Live TV captioning is evaluated by regulatory agencies using various caption evaluation metrics. However, caption evaluation metrics are often not informed by preferences of DHH users or how meaningful the captions are. There is a...
true
[]
[]
Reduced Inequalities
null
null
This material is based on work supported by the Department of Health and Human Services under Award No. 90DPCP0002-0100, and by the National Science Foundation under Award No. DGE-2125362. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessa...
2022
false
false
false
false
false
false
false
false
false
true
false
false
false
false
false
false
false
arora-etal-2020-supervised
https://aclanthology.org/2020.acl-main.696
Supervised Grapheme-to-Phoneme Conversion of Orthographic Schwas in Hindi and Punjabi
Hindi grapheme-to-phoneme (G2P) conversion is mostly trivial, with one exception: whether a schwa represented in the orthography is pronounced or unpronounced (deleted). Previous work has attempted to predict schwa deletion in a rule-based fashion using prosodic or phonetic analysis. We present the first statistical sc...
false
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[]
null
null
null
null
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
zhao-chen-2009-simplex
https://aclanthology.org/N09-2006
A Simplex Armijo Downhill Algorithm for Optimizing Statistical Machine Translation Decoding Parameters
We propose a variation of simplex-downhill algorithm specifically customized for optimizing parameters in statistical machine translation (SMT) decoder for better end-user automatic evaluation metric scores for translations, such as versions of BLEU, TER and mixtures of them. Traditional simplexdownhill has the advanta...
false
[]
[]
null
null
null
null
2009
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
clarke-lapata-2006-constraint
https://aclanthology.org/P06-2019
Constraint-Based Sentence Compression: An Integer Programming Approach
The ability to compress sentences while preserving their grammaticality and most of their meaning has recently received much attention. Our work views sentence compression as an optimisation problem. We develop an integer programming formulation and infer globally optimal compressions in the face of linguistically moti...
false
[]
[]
null
null
null
Thanks to Jean Carletta, Amit Dubey, Frank Keller, Steve Renals, and Sebastian Riedel for helpful comments and suggestions. Lapata acknowledges the support of EPSRC (grant GR/T04540/01).
2006
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
saif-etal-2014-stopwords
http://www.lrec-conf.org/proceedings/lrec2014/pdf/292_Paper.pdf
On Stopwords, Filtering and Data Sparsity for Sentiment Analysis of Twitter
Sentiment classification over Twitter is usually affected by the noisy nature (abbreviations, irregular forms) of tweets data. A popular procedure to reduce the noise of textual data is to remove stopwords by using pre-compiled stopword lists or more sophisticated methods for dynamic stopword identification. However, t...
false
[]
[]
null
null
null
This work was supported by the EU-FP7 project SENSE4US (grant no. 611242).
2014
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
sennrich-haddow-2016-linguistic
https://aclanthology.org/W16-2209
Linguistic Input Features Improve Neural Machine Translation
Neural machine translation has recently achieved impressive results, while using little in the way of external linguistic information. In this paper we show that the strong learning capability of neural MT models does not make linguistic features redundant; they can be easily incorporated to provide further improvement...
false
[]
[]
null
null
null
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreements 645452 (QT21), and 644402 (HimL).
2016
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
heylen-etal-2014-termwise
http://www.lrec-conf.org/proceedings/lrec2014/pdf/706_Paper.pdf
TermWise: A CAT-tool with Context-Sensitive Terminological Support.
Increasingly, large bilingual document collections are being made available online, especially in the legal domain. This type of Big Data is a valuable resource that specialized translators exploit to search for informative examples of how domain-specific expressions should be translated. However, general purpose searc...
false
[]
[]
null
null
null
null
2014
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
sabir-etal-2021-reinforcebug
https://aclanthology.org/2021.naacl-main.477
ReinforceBug: A Framework to Generate Adversarial Textual Examples
Adversarial Examples (AEs) generated by perturbing original training examples are useful in improving the robustness of Deep Learning (DL) based models. Most prior works generate AEs that are either unconscionable due to lexical errors or semantically and functionally deviant from original examples. In this paper, we p...
false
[]
[]
null
null
null
This work was supported with super-computing resources provided by the Phoenix HPC service at the University of Adelaide.
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
matero-etal-2019-suicide
https://aclanthology.org/W19-3005
Suicide Risk Assessment with Multi-level Dual-Context Language and BERT
Mental health predictive systems typically model language as if from a single context (e.g. Twitter posts, status updates, or forum posts) and often limited to a single level of analysis (e.g. either the message-level or userlevel). Here, we bring these pieces together to explore the use of open-vocabulary (BERT embedd...
true
[]
[]
Good Health and Well-Being
null
null
null
2019
false
false
true
false
false
false
false
false
false
false
false
false
false
false
false
false
false
leonova-zuters-2021-frustration
https://aclanthology.org/2021.ranlp-1.93
Frustration Level Annotation in Latvian Tweets with Non-Lexical Means of Expression
We present a neural-network-driven model for annotating frustration intensity in customer support tweets, based on representing tweet texts using a bag-ofwords encoding after processing with subword segmentation together with nonlexical features. The model was evaluated on tweets in English and Latvian languages, focus...
false
[]
[]
null
null
null
The research has been supported by the European Regional Development Fund within the joint project of SIA TILDE and University of Latvia "Multilingual Artificial Intelligence Based Human Computer Interaction" No.1.1.1.1/18/A/148.
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
maillette-de-buy-wenniger-simaan-2013-formal
https://aclanthology.org/W13-0807
A Formal Characterization of Parsing Word Alignments by Synchronous Grammars with Empirical Evidence to the ITG Hypothesis.
Deciding whether a synchronous grammar formalism generates a given word alignment (the alignment coverage problem) depends on finding an adequate instance grammar and then using it to parse the word alignment. But what does it mean to parse a word alignment by a synchronous grammar? This is formally undefined until we ...
false
[]
[]
null
null
null
We thank reviewers for their helpful comments, and thank Mark-Jan Nederhof for illuminating discussions on parsing as intersection. This work is supported by The Netherlands Organization for Scientific Research (NWO) under grant nr. 612.066.929.
2013
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ciobotaru-dinu-2021-red
https://aclanthology.org/2021.ranlp-1.34
RED: A Novel Dataset for Romanian Emotion Detection from Tweets
In Romanian language there are some resources for automatic text comprehension, but for Emotion Detection, not lexicon-based, there are none. To cover this gap, we extracted data from Twitter and created the first dataset containing tweets annotated with five types of emotions: joy, fear, sadness, anger and neutral, wi...
false
[]
[]
null
null
null
We would like to thank Nicu Ciobotaru and Ioana Alexandra Rȃducanu for their help with the annotation process, Ligia Maria Bȃtrînca for proof reading and suggestions, as well as the anonymous reviewers for their time and valuable comments.We acknowledge the support of a grant of the Romanian Ministry of Education and R...
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
hattasch-etal-2020-summarization
https://aclanthology.org/2020.lrec-1.827
Summarization Beyond News: The Automatically Acquired Fandom Corpora
Large state-of-the-art corpora for training neural networks to create abstractive summaries are mostly limited to the news genre, as it is expensive to acquire human-written summaries for other types of text at a large scale. In this paper, we present a novel automatic corpus construction approach to tackle this issue ...
false
[]
[]
null
null
null
This work has been supported by the German Research Foundation as part of the Research Training Group Adaptive Preparation of Information from Heterogeneous Sources (AIPHES) under grant No. GRK 1994/1. Thanks to Aurel Kilian and Ben Kohr who helped with the implementation of the first prototype and to all human annotat...
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
neill-2019-lda
https://aclanthology.org/W19-7505
LDA Topic Modeling for pram\=aṇa Texts: A Case Study in Sanskrit NLP Corpus Building
Sanskrit texts in epistemology, metaphysics, and logic (i.e., pramāṇa texts) remain underrepresented in computational work. To begin to remedy this, a 3.5 million-token digital corpus has been prepared for document-and word-level analysis, and its potential demonstrated through Latent Dirichlet Allocation (LDA) topic m...
false
[]
[]
null
null
null
null
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
zhao-etal-2020-spanmlt
https://aclanthology.org/2020.acl-main.296
SpanMlt: A Span-based Multi-Task Learning Framework for Pair-wise Aspect and Opinion Terms Extraction
Aspect terms extraction and opinion terms extraction are two key problems of fine-grained Aspect Based Sentiment Analysis (ABSA). The aspect-opinion pairs can provide a global profile about a product or service for consumers and opinion mining systems. However, traditional methods can not directly output aspect-opinion...
false
[]
[]
null
null
null
This research is supported in part by the National Natural Science Foundation of China under Grant 61702500.
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ye-etal-2020-safer
https://aclanthology.org/2020.acl-main.317
SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions
State-of-the-art NLP models can often be fooled by human-unaware transformations such as synonymous word substitution. For security reasons, it is of critical importance to develop models with certified robustness that can provably guarantee that the prediction is can not be altered by any possible synonymous word subs...
false
[]
[]
null
null
null
This work is supported in part by NSF CRII 1830161 and NSF CAREER 1846421.
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
siegel-1997-learning
https://aclanthology.org/W97-0318
Learning Methods for Combining Linguistic Indicators to Classify Verbs
Fourteen linguistically-motivated numerical indicators are evaluated for their ability to categorize verbs as either states or events. The values for each indicator are computed automatically across a corpus of text. To improve classification performance, machine learning techniques are employed to combine multiple ind...
false
[]
[]
null
null
null
Kathleen R. McKeown was extremely helpful regarding the formulation of our work and Judith Klavans regarding linguistic techniques. Alexander D. Charfee, Vasileios Hatzivassiloglou, Dragomir Radev and Dekai Wu provided many helpful insights regarding the evaluation and presentation of our results.This research is suppo...
1997
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
tiedemann-2013-experiences
https://aclanthology.org/W13-5606
Experiences in Building the Let's MT! Portal on Amazon EC2
In this presentation I will discuss the design and implementation of Let's MT!, a collaborative platform for building statistical machine translation systems. The goal of this platform is to make MT technology, that has been developed in academia, accessible for professional translators, freelancers and everyday users ...
false
[]
[]
null
null
null
null
2013
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
liu-etal-2021-dexperts
https://aclanthology.org/2021.acl-long.522
DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts
Despite recent advances in natural language generation, it remains challenging to control attributes of generated text. We propose DEX-PERTS: Decoding-time Experts, a decodingtime method for controlled text generation that combines a pretrained language model with "expert" LMs and/or "anti-expert" LMs in a product of e...
false
[]
[]
null
null
null
This research is supported in part by NSF (IIS-1714566), DARPA MCS program through NIWC Pacific (N66001-19-2-4031), and Allen Institute for AI. We thank OpenAI, specifically Bianca Martin and Miles Brundage, for providing access to GPT-3 through the OpenAI API Academic Access Program. We also thank UW NLP, AI2 Mosaic, ...
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
liu-seneff-2009-review
https://aclanthology.org/D09-1017
Review Sentiment Scoring via a Parse-and-Paraphrase Paradigm
This paper presents a parse-and-paraphrase paradigm to assess the degrees of sentiment for product reviews. Sentiment identification has been well studied; however, most previous work provides binary polarities only (positive and negative), and the polarity of sentiment is simply reversed when a negation is detected. T...
false
[]
[]
null
null
null
null
2009
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
pratt-pacak-1969-automated
https://aclanthology.org/C69-1101
Automated Processing of Medical English
Int ro duct ion The present interest of the scientific community in automated language processing has been awakened by the enormous capabilities of the high speed digltal computer. It was recognized that the computer which has the capacity to handle symbols effectively can also treat words as symbols and language as a ...
true
[]
[]
Good Health and Well-Being
null
null
null
1969
false
false
true
false
false
false
false
false
false
false
false
false
false
false
false
false
false
christensen-etal-2014-hierarchical
https://aclanthology.org/P14-1085
Hierarchical Summarization: Scaling Up Multi-Document Summarization
Multi-document summarization (MDS) systems have been designed for short, unstructured summaries of 10-15 documents, and are inadequate for larger document collections. We propose a new approach to scaling up summarization called hierarchical summarization, and present the first implemented system, SUMMA. SUMMA produces...
false
[]
[]
null
null
null
We thank Amitabha Bagchi, Niranjan Balasubramanian, Danish Contractor, Oren Etzioni, Tony Fader, Carlos Guestrin, Prachi Jain, Lucy Vanderwende, Luke Zettlemoyer, and the anonymous reviewers for their helpful suggestions and feedback. We thank Hui Lin and Jeff Bilmes for providing us with their code. This research was ...
2014
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
johnson-1984-discovery
https://aclanthology.org/P84-1070
A Discovery Procedure for Certain Phonological Rules
Acquisition of phonological systems can be insightfully studied in terms of discovery procedures. This paper describes a discovery procedure, implemented in Lisp, capable of determining a set of ordered phonological rules, which may be in opaque contexts~ from a set of surface forms arranged in paradigms. 1.
false
[]
[]
null
null
null
null
1984
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
adams-etal-2020-induced
https://aclanthology.org/2020.sigmorphon-1.25
Induced Inflection-Set Keyword Search in Speech
We investigate the problem of searching for a lexeme-set in speech by searching for its inflectional variants. Experimental results indicate how lexeme-set search performance changes with the number of hypothesized inflections, while ablation experiments highlight the relative importance of different components in the ...
false
[]
[]
null
null
null
We would like to thank all reviewers for their constructive feedback.
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
aggarwal-etal-2020-sukhan
https://aclanthology.org/2020.icon-main.29
SUKHAN: Corpus of Hindi Shayaris annotated with Sentiment Polarity Information
Shayari is a form of poetry mainly popular in the Indian subcontinent, in which the poet expresses his emotions and feelings in a very poetic manner. It is one of the best ways to express our thoughts and opinions. Therefore, it is of prime importance to have an annotated corpus of Hindi shayaris for the task of sentim...
false
[]
[]
null
null
null
null
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ramanand-etal-2010-wishful
https://aclanthology.org/W10-0207
Wishful Thinking - Finding suggestions and 'buy' wishes from product reviews
This paper describes methods aimed at solving the novel problem of automatically discovering 'wishes' from (English) documents such as reviews or customer surveys. These wishes are sentences in which authors make suggestions (especially for improvements) about a product or service or show intentions to purchase a produ...
false
[]
[]
null
null
null
null
2010
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
channarukul-etal-2000-enriching
https://aclanthology.org/W00-1422
Enriching partially-specified representations for text realization using an attribute grammar
We present a new approach to enriching underspecified representations of content to be realized as text. Our approach uses an attribute grammar to propagate missing information where needed in a tree that represents the text to be realized. This declaratively-specified grammar mediates between application-produced outp...
false
[]
[]
null
null
null
The authors are indebted to John T. Boyland for his helpful comments and suggestions.
2000
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
xu-etal-2021-adaptive
https://aclanthology.org/2021.emnlp-main.198
Adaptive Bridge between Training and Inference for Dialogue Generation
Although exposure bias has been widely studied in some NLP tasks, it faces its unique challenges in dialogue response generation, the representative one-to-various generation scenario. In real human dialogue, there are many appropriate responses for the same context, not only with different expressions, but also with d...
false
[]
[]
null
null
null
This work is supported by the Beijing Academy of Artificial Intelligence (BAAI), and the National Natural Science Foundation of China (NSFC) (No.61773362).
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
davoodi-kosseim-2016-contribution
https://aclanthology.org/W16-3620
On the Contribution of Discourse Structure on Text Complexity Assessment
This paper investigates the influence of discourse features on text complexity assessment. To do so, we created two data sets based on the Penn Discourse Treebank and the Simple English Wikipedia corpora and compared the influence of coherence, cohesion, surface, lexical and syntactic features to assess text complexity...
false
[]
[]
null
null
null
The authors would like to thank the anonymous reviewers for their feedback on the paper. This work was financially supported by NSERC.
2016
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
buck-vlachos-2021-trajectory
https://aclanthology.org/2021.adaptnlp-1.15
Trajectory-Based Meta-Learning for Out-Of-Vocabulary Word Embedding Learning
Word embedding learning methods require a large number of occurrences of a word to accurately learn its embedding. However, outof-vocabulary (OOV) words which do not appear in the training corpus emerge frequently in the smaller downstream data. Recent work formulated OOV embedding learning as a fewshot regression prob...
false
[]
[]
null
null
null
null
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
kondratyuk-2019-cross
https://aclanthology.org/W19-4203
Cross-Lingual Lemmatization and Morphology Tagging with Two-Stage Multilingual BERT Fine-Tuning
We present our CHARLES-SAARLAND system for the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology, in task 2, Morphological Analysis and Lemmatization in Context. We leverage the multilingual BERT model and apply several fine-tuning strategies introduced by UDify demonstrating exceptional evaluati...
false
[]
[]
null
null
null
Daniel Kondratyuk has been supported by the Erasmus Mundus program in Language & Communication Technologies (LCT).
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
gardner-etal-2020-determining
https://aclanthology.org/2020.wnut-1.4
Determining Question-Answer Plausibility in Crowdsourced Datasets Using Multi-Task Learning
Datasets extracted from social networks and online forums are often prone to the pitfalls of natural language, namely the presence of unstructured and noisy data. In this work, we seek to enable the collection of high-quality question-answer datasets from social media by proposing a novel task for automated quality ana...
false
[]
[]
null
null
null
null
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
zhang-lapata-2014-chinese
https://aclanthology.org/D14-1074
Chinese Poetry Generation with Recurrent Neural Networks
We propose a model for Chinese poem generation based on recurrent neural networks which we argue is ideally suited to capturing poetic content and form. Our generator jointly performs content selection ("what to say") and surface realization ("how to say") by learning representations of individual characters, and their...
false
[]
[]
null
null
null
We would like to thank Eva Halser for valuable discussions on the machine translation baseline. We are grateful to the 30 Chinese poetry experts for participating in our rating study. Thanks to Gujing Lu, Chu Liu, and Yibo Wang for their help with translating the poems in Table 6 and Table 1.
2014
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
takehisa-2017-remarks
https://aclanthology.org/Y17-1028
Remarks on Denominal -Ed Adjectives
This paper discusses denominal adjectives derived by affixation of-ed in English in light of recent advances in linguistic theory and makes the following three claims. First, unlike recent proposals arguing against their denominal status, the paper defends the widely held view that these adjectives are derived from nom...
false
[]
[]
null
null
null
I am grateful to an anonymous reviewer for providing invaluable comments on an earlier version of this paper. The usual disclaimers apply.
2017
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
yan-etal-2021-adatag
https://aclanthology.org/2021.acl-long.362
AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decoding
Automatic extraction of product attribute values is an important enabling technology in e-Commerce platforms. This task is usually modeled using sequence labeling architectures, with several extensions to handle multi-attribute extraction. One line of previous work constructs attribute-specific models, through separate...
false
[]
[]
null
null
null
This work has been supported in part by NSF SMA 18-29268. We would like to thank Jun Ma, Chenwei Zhang, Colin Lockard, Pascual Martínez-Gómez, Binxuan Huang from Amazon, and all the collaborators in USC INK research lab, for their constructive feedback on the work. We would also like to thank the anonymous reviewers fo...
2021
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
chen-kageura-2020-multilingualization
https://aclanthology.org/2020.lrec-1.512
Multilingualization of Medical Terminology: Semantic and Structural Embedding Approaches
The multilingualization of terminology is an essential step in the translation pipeline, to ensure the correct transfer of domain-specific concepts. Many institutions and language service providers construct and maintain multilingual terminologies, which constitute important assets. However, the curation of such multil...
true
[]
[]
Good Health and Well-Being
null
null
null
2020
false
false
true
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ge-etal-2013-event
https://aclanthology.org/D13-1001
Event-Based Time Label Propagation for Automatic Dating of News Articles
Since many applications such as timeline summaries and temporal IR involving temporal analysis rely on document timestamps, the task of automatic dating of documents has been increasingly important. Instead of using feature-based methods as conventional models, our method attempts to date documents in a year level by e...
false
[]
[]
null
null
null
We thank the anonymous reviewers for their valuable suggestions. This paper is supported by NSFC Project 61075067, NSFC Project 61273318 and National Key Technology R&D Program (No: 2011BAH10B04-03).
2013
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
murveit-etal-1991-speech
https://aclanthology.org/H91-1015
Speech Recognition in SRI's Resource Management and ATIS Systems
This paper describes improvements to DECIPHER, the speech recognition component in SKI's Air Travel Information Systems (ATIS) and Resource Management systems. DECIPHER is a speaker-independent continuous speech recognition system based on hidden Markov model (HMM) technology. We show significant performance improvemen...
false
[]
[]
null
null
null
null
1991
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
meile-1961-problems
https://aclanthology.org/1961.earlymt-1.21
On problems of address in an automatic dictionary of French
In most printed dictionaries, the address of each article, that is of each set of information pertaining to that particular entry, is simply the word itself. It has to be so in a book for common use: for the general reader's sake, the word must be entered in its complete form. In the case of long words, part only of th...
false
[]
[]
null
null
null
null
1961
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
bosch-etal-2006-towards
http://www.lrec-conf.org/proceedings/lrec2006/pdf/597_pdf.pdf
Towards machine-readable lexicons for South African Bantu languages
Lexical information for South African Bantu languages is not readily available in the form of machine-readable lexicons. At present the availability of lexical information is restricted to a variety of paper dictionaries. These dictionaries display considerable diversity in the organisation and representation of data. ...
false
[]
[]
null
null
null
This material is based upon work supported by the National Research Foundation under grant number 2053403. Any opinion, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Research Foundation.
2006
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
liu-haghighi-2011-ordering
https://aclanthology.org/P11-1111
Ordering Prenominal Modifiers with a Reranking Approach
In this work, we present a novel approach to the generation task of ordering prenominal modifiers. We take a maximum entropy reranking approach to the problem which admits arbitrary features on a permutation of modifiers, exploiting hundreds of thousands of features in total. We compare our error rates to the state-of-...
false
[]
[]
null
null
null
Many thanks to Margaret Mitchell, Regina Barzilay, Xiao Chen, and members of the CSAIL NLP group for their help and suggestions.
2011
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
song-etal-2012-joint
https://aclanthology.org/D12-1114
Joint Learning for Coreference Resolution with Markov Logic
Pairwise coreference resolution models must merge pairwise coreference decisions to generate final outputs. Traditional merging methods adopt different strategies such as the bestfirst method and enforcing the transitivity constraint, but most of these methods are used independently of the pairwise learning methods as ...
false
[]
[]
null
null
null
Part of the work was done when the first author was a visiting student in the Singapore Management University. And this work was partially supported by the National High Technology Research and Development Program of China(863 Program) (No.2012AA011101), the National Natural Science Foundation of China (No.91024009, No...
2012
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
velardi-etal-2012-new
http://www.lrec-conf.org/proceedings/lrec2012/pdf/295_Paper.pdf
A New Method for Evaluating Automatically Learned Terminological Taxonomies
Evaluating a taxonomy learned automatically against an existing gold standard is a very complex problem, because differences stem from the number, label, depth and ordering of the taxonomy nodes. In this paper we propose casting the problem as one of comparing two hierarchical clusters. To this end we defined a variati...
false
[]
[]
null
null
null
Roberto Navigli and Stefano Faralli gratefully acknowledge the support of the ERC Starting Grant MultiJEDI No. 259234.
2012
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
cettolo-etal-2015-iwslt
https://aclanthology.org/2015.iwslt-evaluation.1
The IWSLT 2015 Evaluation Campaign
null
false
[]
[]
null
null
null
null
2015
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
saers-wu-2013-unsupervised-learning
https://aclanthology.org/2013.iwslt-papers.15
Unsupervised learning of bilingual categories in inversion transduction grammar induction
We present the first known experiments incorporating unsupervised bilingual nonterminal category learning within end-to-end fully unsupervised transduction grammar induction using matched training and testing models. Despite steady recent progress, such induction experiments until now have not allowed for learning diff...
false
[]
[]
null
null
null
This material is based upon work supported in part by the Defense Advanced Research Projects Agency (DARPA) under BOLT contract no. HR0011-12-C-0016, and GALE contract nos. HR0011-06-C-0022 and HR0011-06-C-0023; by the European Union under the FP7 grant agreement no. 287658; and by the Hong Kong Research Grants Council...
2013
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
arumae-liu-2019-guiding
https://aclanthology.org/N19-1264
Guiding Extractive Summarization with Question-Answering Rewards
Highlighting while reading is a natural behavior for people to track salient content of a document. It would be desirable to teach an extractive summarizer to do the same. However, a major obstacle to the development of a supervised summarizer is the lack of ground-truth. Manual annotation of extraction units is costpr...
false
[]
[]
null
null
null
null
2019
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
mann-1981-two
https://aclanthology.org/P81-1012
Two Discourse Generators
The task of discourse generation is to produce multisentential text in natural language which (when heard or read) produces effects (informing, motivating, etc.) and impressions (conciseness, correctness, ease of reading, etc.) which are appropriate to a need or goal held by the creator of the text. Because even little...
false
[]
[]
null
null
null
null
1981
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
khosla-rose-2020-using
https://aclanthology.org/2020.codi-1.3
Using Type Information to Improve Entity Coreference Resolution
Coreference resolution (CR) is an essential part of discourse analysis. Most recently, neural approaches have been proposed to improve over SOTA models from earlier paradigms. So far none of the published neural models leverage external semantic knowledge such as type information. This paper offers the first such model...
false
[]
[]
null
null
null
We thank the anonymous reviewers for their insightful comments. We are also grateful to the members of the TELEDIA group at LTI, CMU for the invaluable feedback. This work was funded in part by Dow Chemical, and Microsoft.
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ye-etal-2016-interactive
https://aclanthology.org/C16-1169
Interactive-Predictive Machine Translation based on Syntactic Constraints of Prefix
Interactive-predictive machine translation (IPMT) is a translation mode which combines machine translation technology and human behaviours. In the IPMT system, the utilization of the prefix greatly affects the interaction efficiency. However, state-of-the-art methods filter translation hypotheses mainly according to th...
false
[]
[]
null
null
null
This work is supported by the National Natural Science Foundation of China (No. 61402299). We would like to thank the anonymous reviewers for their insightful and constructive comments. We also want to thank Yapeng Zhang for help in the preparation of experimental systems in this paper.
2016
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
li-etal-2016-extending
https://aclanthology.org/W16-0602
Extending Phrase-Based Translation with Dependencies by Using Graphs
In this paper, we propose a graph-based translation model which takes advantage of discontinuous phrases. The model segments a graph which combines bigram and dependency relations into subgraphs and produces translations by combining translations of these subgraphs. Experiments on Chinese-English and German-English tas...
false
[]
[]
null
null
null
This research has received funding from the People Programme (
2016
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
duma-menzel-2017-sef
https://aclanthology.org/S17-2024
SEF@UHH at SemEval-2017 Task 1: Unsupervised Knowledge-Free Semantic Textual Similarity via Paragraph Vector
This paper describes our unsupervised knowledge-free approach to the SemEval-2017 Task 1 Competition. The proposed method makes use of Paragraph Vector for assessing the semantic similarity between pairs of sentences. We experimented with various dimensions of the vector and three state-of-the-art similarity metrics. G...
false
[]
[]
null
null
null
null
2017
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
denero-etal-2006-generative
https://aclanthology.org/W06-3105
Why Generative Phrase Models Underperform Surface Heuristics
We investigate why weights from generative models underperform heuristic estimates in phrasebased machine translation. We first propose a simple generative, phrase-based model and verify that its estimates are inferior to those given by surface statistics. The performance gap stems primarily from the addition of a hidd...
false
[]
[]
null
null
null
null
2006
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
atwell-drakos-1987-pattern
https://aclanthology.org/E87-1010
Pattern Recognition Applied to the Acquisition of a Grammatical Classification System From Unrestricted English Text
Within computational linguistics, the use of statistical pattern matching is generally restricted to speech processing. We have attempted to apply statistical techniques to discover a grammatical classification system from a Corpus of 'raw' English text. A discovery procedure is simpler for a simpler
false
[]
[]
null
null
null
null
1987
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
varanasi-etal-2020-copybert
https://aclanthology.org/2020.nlp4convai-1.3
CopyBERT: A Unified Approach to Question Generation with Self-Attention
Contextualized word embeddings provide better initialization for neural networks that deal with various natural language understanding (NLU) tasks including question answering (QA) and more recently, question generation (QG). Apart from providing meaningful word representations, pre-trained transformer models, such as ...
false
[]
[]
null
null
null
The authors would like to thank the anonymous reviewers for helpful feedback. The work was partially funded by the German Federal Ministry of Education and Research (BMBF) through the project DEEPLEE (01IW17001).
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
ager-etal-2018-modelling
https://aclanthology.org/K18-1051
Modelling Salient Features as Directions in Fine-Tuned Semantic Spaces
In this paper we consider semantic spaces consisting of objects from some particular domain (e.g. IMDB movie reviews). Various authors have observed that such semantic spaces often model salient features (e.g. how scary a movie is) as directions. These feature directions allow us to rank objects according to how much t...
false
[]
[]
null
null
null
This work has been supported by ERC Starting Grant 637277.
2018
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
dirkson-2019-knowledge
https://aclanthology.org/P19-2009
Knowledge Discovery and Hypothesis Generation from Online Patient Forums: A Research Proposal
The unprompted patient experiences shared on patient forums contain a wealth of unexploited knowledge. Mining this knowledge and crosslinking it with biomedical literature, could expose novel insights, which could subsequently provide hypotheses for further clinical research. As of yet, automated methods for open knowl...
true
[]
[]
Good Health and Well-Being
null
null
null
2019
false
false
true
false
false
false
false
false
false
false
false
false
false
false
false
false
false
symonds-etal-2011-modelling
https://aclanthology.org/Y11-1033
Modelling Word Meaning using Efficient Tensor Representations
Models of word meaning, built from a corpus of text, have demonstrated success in emulating human performance on a number of cognitive tasks. Many of these models use geometric representations of words to store semantic associations between words. Often word order information is not captured in these models. The lack o...
false
[]
[]
null
null
null
null
2011
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
lin-2004-computational
https://aclanthology.org/N04-2004
A Computational Framework for Non-Lexicalist Semantics
Under a lexicalist approach to semantics, a verb completely encodes its syntactic and semantic structures, along with the relevant syntax-tosemantics mapping; polysemy is typically attributed to the existence of different lexical entries. A lexicon organized in this fashion contains much redundant information and is un...
false
[]
[]
null
null
null
null
2004
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
makrai-etal-2013-applicative
https://aclanthology.org/W13-3207
Applicative structure in vector space models
We introduce a new 50-dimensional embedding obtained by spectral clustering of a graph describing the conceptual structure of the lexicon. We use the embedding directly to investigate sets of antonymic pairs, and indirectly to argue that function application in CVSMs requires not just vectors but two transformations (c...
false
[]
[]
null
null
null
Makrai did the work on antonym set testing, Nemeskey built the embedding, Kornai advised. We would like to thank Zsófia Tardos (BUTE) and the anonymous reviewers for useful comments. Work supported by OTKA grant #82333.
2013
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
libovicky-etal-2020-expand
https://aclanthology.org/2020.ngt-1.18
Expand and Filter: CUNI and LMU Systems for the WNGT 2020 Duolingo Shared Task
We present our submission to the Simultaneous Translation And Paraphrase for Language Education (STAPLE) challenge. We used a standard Transformer model for translation, with a crosslingual classifier predicting correct translations on the output n-best list. To increase the diversity of the outputs, we used additional...
true
[]
[]
Quality Education
null
null
null
2020
false
false
false
true
false
false
false
false
false
false
false
false
false
false
false
false
false
varadi-2000-lexical
http://www.lrec-conf.org/proceedings/lrec2000/pdf/122.pdf
Lexical and Translation Equivalence in Parallel Corpora
In the present paper we intend to investigate to what extent use of parallel corpora can help to eliminate some of the difficulties noted with bilingual dictionaries. The particular issues addressed are the bidirectionality of translation equivalence, the coverage of multiword units, and the amount of implicit knowledg...
false
[]
[]
null
null
null
The research reported in the paper was supported by Országos Tudományos Kutatási Alapprogramok (grant number T026091).
2000
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
choi-etal-1999-english
https://aclanthology.org/1999.mtsummit-1.64
English-to-Korean Web translator : ``FromTo/Web-EK''
The previous English-Korean MT system that have been developed in Korea have dealt with only written text as translation object. Most of them enumerated a following list of the problems that had not seemed to be easy to solve in the near future : 1) processing of non-continuous idiomatic expressions 2) reduction of too...
false
[]
[]
null
null
null
null
1999
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
tanase-etal-2020-upb
https://aclanthology.org/2020.semeval-1.296
UPB at SemEval-2020 Task 12: Multilingual Offensive Language Detection on Social Media by Fine-tuning a Variety of BERT-based Models
Offensive language detection is one of the most challenging problem in the natural language processing field, being imposed by the rising presence of this phenomenon in online social media. This paper describes our Transformer-based solutions for identifying offensive language on Twitter in five languages (i.e., Englis...
true
[]
[]
Peace, Justice and Strong Institutions
null
null
null
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
true
false
ahlberg-enache-2012-combining
http://www.lrec-conf.org/proceedings/lrec2012/pdf/360_Paper.pdf
Combining Language Resources Into A Grammar-Driven Swedish Parser
This paper describes work on a rule-based, open-source parser for Swedish. The central component is a wide-coverage grammar implemented in the GF formalism (Grammatical Framework), a dependently typed grammar formalism based on Martin-Löf type theory. GF has strong support for multilinguality and has so far been used s...
false
[]
[]
null
null
null
The work has been funded by Center of Language Technology. We would also like to give special thanks to Aarne Ranta, Elisabet Engdahl, Krasimir Angelov, Olga Caprotti, Lars Borin and John Camilleri for their help and support.
2012
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
sinopalnikova-smrz-2006-intelligent
http://www.lrec-conf.org/proceedings/lrec2006/pdf/275_pdf.pdf
Intelligent Dictionary Interfaces: Usability Evaluation of Access-Supporting Enhancements
The present paper describes psycholinguistic experiments aimed at exploring the way people behave while accessing electronic dictionaries. In our work we focused on the access by meaning that, in comparison with the access by form, is currently less studied and very seldom implemented in modern dictionary interfaces. T...
false
[]
[]
null
null
null
null
2006
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
boldrini-etal-2010-emotiblog
https://aclanthology.org/W10-1801
EmotiBlog: A Finer-Grained and More Precise Learning of Subjectivity Expression Models
The exponential growth of the subjective information in the framework of the Web 2.0 has led to the need to create Natural Language Processing tools able to analyse and process such data for multiple practical applications. They require training on specifically annotated corpora, whose level of detail must be fine enou...
false
[]
[]
null
null
null
null
2010
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
tufis-etal-2020-collection
https://aclanthology.org/2020.lrec-1.337
Collection and Annotation of the Romanian Legal Corpus
We present the Romanian legislative corpus which is a valuable linguistic asset for the development of machine translation systems, especially for under-resourced languages. The knowledge that can be extracted from this resource is necessary for a deeper understanding of how law terminology is used and how it can be ma...
true
[]
[]
Peace, Justice and Strong Institutions
null
null
This research was supported by the EC grant no. INEA/CEF/ICT/A2017/1565710 for the Action no. 2017-EU-IA-0136 entitled "Multilingual Resources for CEF.AT in the legal domain" (MARCELL).
2020
false
false
false
false
false
false
false
false
false
false
false
false
false
false
false
true
false