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ACL | On Positivity Bias in Negative Reviews | Prior work has revealed that positive words occur more frequently than negative words in human expressions, which is typically attributed to positivity bias, a tendency for people to report positive views of reality. But what about the language used in negative reviews? Consistent with prior work, we show that English ... | c91001a6dec137a0462adb9f32f1d7d2 | 2,021 | [
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ACL | Emerging Cross-lingual Structure in Pretrained Language Models | We study the problem of multilingual masked language modeling, i.e. the training of a single model on concatenated text from multiple languages, and present a detailed study of several factors that influence why these models are so effective for cross-lingual transfer. We show, contrary to what was previously hypothesi... | 2027c89cfc0f898642c7b0ca226b82ed | 2,020 | [
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ACL | Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing | Prior work has explored directly regularizing the output distributions of probabilistic models to alleviate peaky (i.e. over-confident) predictions, a common sign of overfitting. This class of techniques, of which label smoothing is one, has a connection to entropy regularization. Despite the consistent success of labe... | 83fd6bf13b78b9fc5a40f6c7a500b0b5 | 2,020 | [
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ACL | Few-Shot NLG with Pre-Trained Language Model | Neural-based end-to-end approaches to natural language generation (NLG) from structured data or knowledge are data-hungry, making their adoption for real-world applications difficult with limited data. In this work, we propose the new task of few-shot natural language generation. Motivated by how humans tend to summari... | d9f6ba8db645ec2ed182c45550413167 | 2,020 | [
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ACL | Decompositional Argument Mining: A General Purpose Approach for Argument Graph Construction | This work presents an approach decomposing propositions into four functional components and identify the patterns linking those components to determine argument structure. The entities addressed by a proposition are target concepts and the features selected to make a point about the target concepts are aspects. A line ... | dcfba1f0c5f8b5ce0b75de32bee86312 | 2,019 | [
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ACL | A Recipe for Arbitrary Text Style Transfer with Large Language Models | In this paper, we leverage large language models (LLMs) to perform zero-shot text style transfer. We present a prompting method that we call augmented zero-shot learning, which frames style transfer as a sentence rewriting task and requires only a natural language instruction, without model fine-tuning or exemplars in ... | bbc44d5892d1f3fafef55925f61a8c54 | 2,022 | [
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ACL | I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling | To quantify how well natural language understanding models can capture consistency in a general conversation, we introduce the DialoguE COntradiction DEtection task (DECODE) and a new conversational dataset containing both human-human and human-bot contradictory dialogues. We show that: (i) our newly collected dataset ... | 668c747f748345b38aece148464ed8c0 | 2,021 | [
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ACL | TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data | Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-based natural language (NL) understanding tasks. Such models are typically trained on free-form NL text, hence may not be suitable for tasks like semantic parsing over structured data, which require reasoning over both free-form NL ... | 5e13c5f467120e866acc39b9a104eb97 | 2,020 | [
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ACL | Finding Universal Grammatical Relations in Multilingual BERT | Recent work has found evidence that Multilingual BERT (mBERT), a transformer-based multilingual masked language model, is capable of zero-shot cross-lingual transfer, suggesting that some aspects of its representations are shared cross-lingually. To better understand this overlap, we extend recent work on finding synta... | f23071b6dd75c8454d0576736a03c021 | 2,020 | [
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ACL | Can Sequence-to-Sequence Models Crack Substitution Ciphers? | Decipherment of historical ciphers is a challenging problem. The language of the target plaintext might be unknown, and ciphertext can have a lot of noise. State-of-the-art decipherment methods use beam search and a neural language model to score candidate plaintext hypotheses for a given cipher, assuming the plaintext... | 19fbed05d5c1b7f4f2775657b4587597 | 2,021 | [
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ACL | ADEPT: An Adjective-Dependent Plausibility Task | A false contract is more likely to be rejected than a contract is, yet a false key is less likely than a key to open doors. While correctly interpreting and assessing the effects of such adjective-noun pairs (e.g., false key) on the plausibility of given events (e.g., opening doors) underpins many natural language unde... | e16b7234f7e944a88a465bc1e4d55f74 | 2,021 | [
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ACL | Implicit Discourse Relation Identification for Open-domain Dialogues | Discourse relation identification has been an active area of research for many years, and the challenge of identifying implicit relations remains largely an unsolved task, especially in the context of an open-domain dialogue system. Previous work primarily relies on a corpora of formal text which is inherently non-dial... | 50e873998d2953b7fc0aed6005eb95d7 | 2,019 | [
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ACL | Educational Question Generation of Children Storybooks via Question Type Distribution Learning and Event-centric Summarization | Generating educational questions of fairytales or storybooks is vital for improving children’s literacy ability. However, it is challenging to generate questions that capture the interesting aspects of a fairytale story with educational meaningfulness. In this paper, we propose a novel question generation method that f... | 77b46c8186a171757aa3d9b07b972abe | 2,022 | [
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ACL | Flexible Generation from Fragmentary Linguistic Input | The dominant paradigm for high-performance models in novel NLP tasks today is direct specialization for the task via training from scratch or fine-tuning large pre-trained models. But does direct specialization capture how humans approach novel language tasks? We hypothesize that human performance is better characteriz... | e8353359ce15b712a23caa18c8cd5e9d | 2,022 | [
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ACL | PLANET: Dynamic Content Planning in Autoregressive Transformers for Long-form Text Generation | Despite recent progress of pre-trained language models on generating fluent text, existing methods still suffer from incoherence problems in long-form text generation tasks that require proper content control and planning to form a coherent high-level logical flow. In this work, we propose PLANET, a novel generation fr... | 3236fd99c45073e0205f6baff19fcc53 | 2,022 | [
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ACL | Few-shot Named Entity Recognition with Self-describing Networks | Few-shot NER needs to effectively capture information from limited instances and transfer useful knowledge from external resources. In this paper, we propose a self-describing mechanism for few-shot NER, which can effectively leverage illustrative instances and precisely transfer knowledge from external resources by de... | 960ce259671723c637f8003bbd5f8bed | 2,022 | [
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ACL | HYPHEN: Hyperbolic Hawkes Attention For Text Streams | Analyzing the temporal sequence of texts from sources such as social media, news, and parliamentary debates is a challenging problem as it exhibits time-varying scale-free properties and fine-grained timing irregularities. We propose a Hyperbolic Hawkes Attention Network (HYPHEN), which learns a data-driven hyperbolic ... | 3e1e750c9b4580c06a8c45cc49e454f8 | 2,022 | [
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ACL | Transition-based Semantic Dependency Parsing with Pointer Networks | Transition-based parsers implemented with Pointer Networks have become the new state of the art in dependency parsing, excelling in producing labelled syntactic trees and outperforming graph-based models in this task. In order to further test the capabilities of these powerful neural networks on a harder NLP problem, w... | b3a567552d508d7f8e30f0f1454a4620 | 2,020 | [
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ACL | On the Generation of Medical Dialogs for COVID-19 | Under the pandemic of COVID-19, people experiencing COVID19-related symptoms have a pressing need to consult doctors. Because of the shortage of medical professionals, many people cannot receive online consultations timely. To address this problem, we aim to develop a medical dialog system that can provide COVID19-rela... | d580c138304301626f4a4edd3109d0b4 | 2,021 | [
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ACL | Hiring Now: A Skill-Aware Multi-Attention Model for Job Posting Generation | Writing a good job posting is a critical step in the recruiting process, but the task is often more difficult than many people think. It is challenging to specify the level of education, experience, relevant skills per the company information and job description. To this end, we propose a novel task of Job Posting Gene... | 69033db5bc6bd1f7bf8c70610d5e6410 | 2,020 | [
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ACL | Improving Dialog Systems for Negotiation with Personality Modeling | In this paper, we explore the ability to model and infer personality types of opponents, predict their responses, and use this information to adapt a dialog agent’s high-level strategy in negotiation tasks. Inspired by the idea of incorporating a theory of mind (ToM) into machines, we introduce a probabilistic formulat... | 75f8da0efb0df07823d0507b2dc9b052 | 2,021 | [
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ACL | Learning How to Active Learn by Dreaming | Heuristic-based active learning (AL) methods are limited when the data distribution of the underlying learning problems vary. Recent data-driven AL policy learning methods are also restricted to learn from closely related domains. We introduce a new sample-efficient method that learns the AL policy directly on the targ... | 17057d42c7e024a826714da6d1f6b8df | 2,019 | [
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ACL | Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER | Recent advances in prompt-based learning have shown strong results on few-shot text classification by using cloze-style templates.Similar attempts have been made on named entity recognition (NER) which manually design templates to predict entity types for every text span in a sentence. However, such methods may suffer ... | 2a25552ded42e80e4431e2c7733d9174 | 2,022 | [
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ACL | Relative Importance in Sentence Processing | Determining the relative importance of the elements in a sentence is a key factor for effortless natural language understanding. For human language processing, we can approximate patterns of relative importance by measuring reading fixations using eye-tracking technology. In neural language models, gradient-based salie... | 58abbf5992a5ba3130884334308a84cd | 2,021 | [
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ACL | Lightweight Adapter Tuning for Multilingual Speech Translation | Adapter modules were recently introduced as an efficient alternative to fine-tuning in NLP. Adapter tuning consists in freezing pre-trained parameters of a model and injecting lightweight modules between layers, resulting in the addition of only a small number of task-specific trainable parameters. While adapter tuning... | c7391791fa4bcd83c6ebcc804bafb958 | 2,021 | [
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ACL | Zero-Shot Cross-lingual Semantic Parsing | Recent work in cross-lingual semantic parsing has successfully applied machine translation to localize parsers to new languages. However, these advances assume access to high-quality machine translation systems and word alignment tools. We remove these assumptions and study cross-lingual semantic parsing as a zero-shot... | 5f0f8cdf162c6b2a1908992c50f826ea | 2,022 | [
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ACL | Determining Relative Argument Specificity and Stance for Complex Argumentative Structures | Systems for automatic argument generation and debate require the ability to (1) determine the stance of any claims employed in the argument and (2) assess the specificity of each claim relative to the argument context. Existing work on understanding claim specificity and stance, however, has been limited to the study o... | 58167323cc2b95ce8ac87b8f4f5c3be1 | 2,019 | [
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ACL | An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation | We study the interpretability issue of task-oriented dialogue systems in this paper. Previously, most neural-based task-oriented dialogue systems employ an implicit reasoning strategy that makes the model predictions uninterpretable to humans. To obtain a transparent reasoning process, we introduce neuro-symbolic to pe... | 3c159e245cd16a5e6afd633a26615da6 | 2,022 | [
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ACL | Multimodal Quality Estimation for Machine Translation | We propose approaches to Quality Estimation (QE) for Machine Translation that explore both text and visual modalities for Multimodal QE. We compare various multimodality integration and fusion strategies. For both sentence-level and document-level predictions, we show that state-of-the-art neural and feature-based QE f... | 9780c9d13bcd8359dbc9b00c15f7e252 | 2,020 | [
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ACL | Sentence-Level Evidence Embedding for Claim Verification with Hierarchical Attention Networks | Claim verification is generally a task of verifying the veracity of a given claim, which is critical to many downstream applications. It is cumbersome and inefficient for human fact-checkers to find consistent pieces of evidence, from which solid verdict could be inferred against the claim. In this paper, we propose a ... | 46ecd44487c44aadc845b0957a39551d | 2,019 | [
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ACL | You Only Need Attention to Traverse Trees | In recent NLP research, a topic of interest is universal sentence encoding, sentence representations that can be used in any supervised task. At the word sequence level, fully attention-based models suffer from two problems: a quadratic increase in memory consumption with respect to the sentence length and an inability... | 547124183625624fae401a1539bb6503 | 2,019 | [
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ACL | Crawling and Preprocessing Mailing Lists At Scale for Dialog Analysis | This paper introduces the Webis Gmane Email Corpus 2019, the largest publicly available and fully preprocessed email corpus to date. We crawled more than 153 million emails from 14,699 mailing lists and segmented them into semantically consistent components using a new neural segmentation model. With 96% accuracy on 15... | d9c1ca8da4cb36b5f9632f7b3db14328 | 2,020 | [
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ACL | A Mixture-of-Experts Model for Antonym-Synonym Discrimination | Discrimination between antonyms and synonyms is an important and challenging NLP task. Antonyms and synonyms often share the same or similar contexts and thus are hard to make a distinction. This paper proposes two underlying hypotheses and employs the mixture-of-experts framework as a solution. It works on the basis o... | 718bb96e986b168bdcda4943794cb6d3 | 2,021 | [
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ACL | Continual Sequence Generation with Adaptive Compositional Modules | Continual learning is essential for real-world deployment when there is a need to quickly adapt the model to new tasks without forgetting knowledge of old tasks. Existing work on continual sequence generation either always reuses existing parameters to learn new tasks, which is vulnerable to catastrophic forgetting on ... | 529ccaeeb5868478a85a2f81c6a3975a | 2,022 | [
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ACL | SMURF: SeMantic and linguistic UndeRstanding Fusion for Caption Evaluation via Typicality Analysis | The open-ended nature of visual captioning makes it a challenging area for evaluation. The majority of proposed models rely on specialized training to improve human-correlation, resulting in limited adoption, generalizability, and explainabilty. We introduce “typicality”, a new formulation of evaluation rooted in infor... | 5ea5888294af791741f99ae5e9ff1b4e | 2,021 | [
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ACL | Intent Classification and Slot Filling for Privacy Policies | Understanding privacy policies is crucial for users as it empowers them to learn about the information that matters to them. Sentences written in a privacy policy document explain privacy practices, and the constituent text spans convey further specific information about that practice. We refer to predicting the privac... | 3284581e2a6ad98e76c19694d673bcde | 2,021 | [
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ACL | A Risk-Averse Mechanism for Suicidality Assessment on Social Media | Recent studies have shown that social media has increasingly become a platform for users to express suicidal thoughts outside traditional clinical settings. With advances in Natural Language Processing strategies, it is now possible to design automated systems to assess suicide risk. However, such systems may generate ... | 69261737037d84f1c1c8db60ef9a665f | 2,022 | [
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ACL | UnitedQA: A Hybrid Approach for Open Domain Question Answering | To date, most of recent work under the retrieval-reader framework for open-domain QA focuses on either extractive or generative reader exclusively. In this paper, we study a hybrid approach for leveraging the strengths of both models. We apply novel techniques to enhance both extractive and generative readers built upo... | 68aa7ce97b20f50acaf89061d647c2ca | 2,021 | [
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ACL | Smart To-Do: Automatic Generation of To-Do Items from Emails | Intelligent features in email service applications aim to increase productivity by helping people organize their folders, compose their emails and respond to pending tasks. In this work, we explore a new application, Smart-To-Do, that helps users with task management over emails. We introduce a new task and dataset for... | 9859e44201fa0a13faf250cde1abbab3 | 2,020 | [
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ACL | Knowledge Enhanced Reflection Generation for Counseling Dialogues | In this paper, we study the effect of commonsense and domain knowledge while generating responses in counseling conversations using retrieval and generative methods for knowledge integration. We propose a pipeline that collects domain knowledge through web mining, and show that retrieval from both domain-specific and c... | ba2934faacd28d81edb26dad6094beec | 2,022 | [
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ACL | Neural reality of argument structure constructions | In lexicalist linguistic theories, argument structure is assumed to be predictable from the meaning of verbs. As a result, the verb is the primary determinant of the meaning of a clause. In contrast, construction grammarians propose that argument structure is encoded in constructions (or form-meaning pairs) that are di... | 409ffa9b50655e72bed07db9d4b694cd | 2,022 | [
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ACL | Analyzing Political Parody in Social Media | Parody is a figurative device used to imitate an entity for comedic or critical purposes and represents a widespread phenomenon in social media through many popular parody accounts. In this paper, we present the first computational study of parody. We introduce a new publicly available data set of tweets from real poli... | e9942cd77c66d6b0ff7023813e8b1450 | 2,020 | [
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ACL | There’s a Time and Place for Reasoning Beyond the Image | Images are often more significant than only the pixels to human eyes, as we can infer, associate, and reason with contextual information from other sources to establish a more complete picture. For example, in Figure 1, we can find a way to identify the news articles related to the picture through segment-wise understa... | cccae4c4302fe9bd5dca4dbab7c58040 | 2,022 | [
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ACL | Similarity Analysis of Contextual Word Representation Models | This paper investigates contextual word representation models from the lens of similarity analysis. Given a collection of trained models, we measure the similarity of their internal representations and attention. Critically, these models come from vastly different architectures. We use existing and novel similarity mea... | 29efc80c1767875bcc704eb4635d5d5d | 2,020 | [
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ACL | Estimating the influence of auxiliary tasks for multi-task learning of sequence tagging tasks | Multi-task learning (MTL) and transfer learning (TL) are techniques to overcome the issue of data scarcity when training state-of-the-art neural networks. However, finding beneficial auxiliary datasets for MTL or TL is a time- and resource-consuming trial-and-error approach. We propose new methods to automatically asse... | d2d2eb44674880df5241492b23379d63 | 2,020 | [
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ACL | How does BERT’s attention change when you fine-tune? An analysis methodology and a case study in negation scope | Large pretrained language models like BERT, after fine-tuning to a downstream task, have achieved high performance on a variety of NLP problems. Yet explaining their decisions is difficult despite recent work probing their internal representations. We propose a procedure and analysis methods that take a hypothesis of h... | 2c3c5e12ad7ce8f3a49ecc59e3eac913 | 2,020 | [
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ACL | Towards Language Agnostic Universal Representations | When a bilingual student learns to solve word problems in math, we expect the student to be able to solve these problem in both languages the student is fluent in, even if the math lessons were only taught in one language. However, current representations in machine learning are language dependent. In this work, we pre... | 86c1998c1b53f043d2a2d5b5e7f666ab | 2,019 | [
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ACL | Investigating Failures of Automatic Translationin the Case of Unambiguous Gender | Transformer-based models are the modern work horses for neural machine translation (NMT), reaching state of the art across several benchmarks. Despite their impressive accuracy, we observe a systemic and rudimentary class of errors made by current state-of-the-art NMT models with regards to translating from a language ... | 2147e1e5b49e9bcffd76a235dac35d96 | 2,022 | [
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ACL | IrEne: Interpretable Energy Prediction for Transformers | Existing software-based energy measurements of NLP models are not accurate because they do not consider the complex interactions between energy consumption and model execution. We present IrEne, an interpretable and extensible energy prediction system that accurately predicts the inference energy consumption of a wide ... | 10a4b5a948ad41c9cec6341b288b852f | 2,021 | [
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ACL | Assessing the Ability of Self-Attention Networks to Learn Word Order | Self-attention networks (SAN) have attracted a lot of interests due to their high parallelization and strong performance on a variety of NLP tasks, e.g. machine translation. Due to the lack of recurrence structure such as recurrent neural networks (RNN), SAN is ascribed to be weak at learning positional information of ... | 9e551bd336cdd3465975cdfed8d6391a | 2,019 | [
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ACL | Interactive Word Completion for Plains Cree | The composition of richly-inflected words in morphologically complex languages can be a challenge for language learners developing literacy. Accordingly, Lane and Bird (2020) proposed a finite state approach which maps prefixes in a language to a set of possible completions up to the next morpheme boundary, for the inc... | 08e915fd68af0db957cd061385d03ce1 | 2,022 | [
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ACL | Distant Learning for Entity Linking with Automatic Noise Detection | Accurate entity linkers have been produced for domains and languages where annotated data (i.e., texts linked to a knowledge base) is available. However, little progress has been made for the settings where no or very limited amounts of labeled data are present (e.g., legal or most scientific domains). In this work, we... | feae6c8f36487ad13cf19985264d2fd3 | 2,019 | [
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ACL | Interpreting Character Embeddings With Perceptual Representations: The Case of Shape, Sound, and Color | Character-level information is included in many NLP models, but evaluating the information encoded in character representations is an open issue. We leverage perceptual representations in the form of shape, sound, and color embeddings and perform a representational similarity analysis to evaluate their correlation with... | e6e0a7977c10f961131416ec22830163 | 2,022 | [
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ACL | AutoTinyBERT: Automatic Hyper-parameter Optimization for Efficient Pre-trained Language Models | Pre-trained language models (PLMs) have achieved great success in natural language processing. Most of PLMs follow the default setting of architecture hyper-parameters (e.g., the hidden dimension is a quarter of the intermediate dimension in feed-forward sub-networks) in BERT. Few studies have been conducted to explore... | f7824b60122adc85b7b852377fa65915 | 2,021 | [
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ACL | PPT: Pre-trained Prompt Tuning for Few-shot Learning | Prompts for pre-trained language models (PLMs) have shown remarkable performance by bridging the gap between pre-training tasks and various downstream tasks. Among these methods, prompt tuning, which freezes PLMs and only tunes soft prompts, provides an efficient and effective solution for adapting large-scale PLMs to ... | 24a5e45c25d60be8c5bb6ac620c8d838 | 2,022 | [
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ACL | Measuring Fairness of Text Classifiers via Prediction Sensitivity | With the rapid growth in language processing applications, fairness has emerged as an important consideration in data-driven solutions. Although various fairness definitions have been explored in the recent literature, there is lack of consensus on which metrics most accurately reflect the fairness of a system. In this... | 4cf1c96620a32b2a80019908b6188ace | 2,022 | [
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ACL | Iterative Edit-Based Unsupervised Sentence Simplification | We present a novel iterative, edit-based approach to unsupervised sentence simplification. Our model is guided by a scoring function involving fluency, simplicity, and meaning preservation. Then, we iteratively perform word and phrase-level edits on the complex sentence. Compared with previous approaches, our model doe... | f9c9400d80ab3b2f15fb6896d22e4a99 | 2,020 | [
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ACL | Towards Quantifiable Dialogue Coherence Evaluation | Automatic dialogue coherence evaluation has attracted increasing attention and is crucial for developing promising dialogue systems. However, existing metrics have two major limitations: (a) they are mostly trained in a simplified two-level setting (coherent vs. incoherent), while humans give Likert-type multi-level co... | a547cc927191f64f9086cd3f22beb76b | 2,021 | [
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ACL | Learning Web-based Procedures by Reasoning over Explanations and Demonstrations in Context | We explore learning web-based tasks from a human teacher through natural language explanations and a single demonstration. Our approach investigates a new direction for semantic parsing that models explaining a demonstration in a context, rather than mapping explanations to demonstrations. By leveraging the idea of inv... | a302494afcbae4b790c676b95a0c39e9 | 2,020 | [
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ACL | Learning Non-Autoregressive Models from Search for Unsupervised Sentence Summarization | Text summarization aims to generate a short summary for an input text. In this work, we propose a Non-Autoregressive Unsupervised Summarization (NAUS) approach, which does not require parallel data for training. Our NAUS first performs edit-based search towards a heuristically defined score, and generates a summary as ... | ecb1ae946db9ed5b80615e25be8903f6 | 2,022 | [
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ACL | Bridge-Based Active Domain Adaptation for Aspect Term Extraction | As a fine-grained task, the annotation cost of aspect term extraction is extremely high. Recent attempts alleviate this issue using domain adaptation that transfers common knowledge across domains. Since most aspect terms are domain-specific, they cannot be transferred directly. Existing methods solve this problem by a... | b150d01b46783ef11a4d6a7714153ad8 | 2,021 | [
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ACL | Bias Analysis and Mitigation in the Evaluation of Authorship Verification | The PAN series of shared tasks is well known for its continuous and high quality research in the field of digital text forensics. Among others, PAN contributions include original corpora, tailored benchmarks, and standardized experimentation platforms. In this paper we review, theoretically and practically, the authors... | e20fe0e65d3714e59634e498b3c2d9e7 | 2,019 | [
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ACL | Reasoning Over Semantic-Level Graph for Fact Checking | Fact checking is a challenging task because verifying the truthfulness of a claim requires reasoning about multiple retrievable evidence. In this work, we present a method suitable for reasoning about the semantic-level structure of evidence. Unlike most previous works, which typically represent evidence sentences with... | 389d189cb0a42bf4587c82d753ba2d38 | 2,020 | [
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ACL | Dependency Parsing as MRC-based Span-Span Prediction | Higher-order methods for dependency parsing can partially but not fully address the issue that edges in dependency trees should be constructed at the text span/subtree level rather than word level. In this paper, we propose a new method for dependency parsing to address this issue. The proposed method constructs depend... | afcfd9ffb0b09dbaee98d018a0ad984d | 2,022 | [
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ACL | Enhancing Entity Boundary Detection for Better Chinese Named Entity Recognition | In comparison with English, due to the lack of explicit word boundary and tenses information, Chinese Named Entity Recognition (NER) is much more challenging. In this paper, we propose a boundary enhanced approach for better Chinese NER. In particular, our approach enhances the boundary information from two perspective... | d9917a660cff9d7aa6c234a4513a7395 | 2,021 | [
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ACL | Evaluating Factuality in Text Simplification | Automated simplification models aim to make input texts more readable. Such methods have the potential to make complex information accessible to a wider audience, e.g., providing access to recent medical literature which might otherwise be impenetrable for a lay reader. However, such models risk introducing errors into... | a2500da6f70d29331d1a75401d056b1e | 2,022 | [
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ACL | Fine-Grained Spoiler Detection from Large-Scale Review Corpora | This paper presents computational approaches for automatically detecting critical plot twists in reviews of media products. First, we created a large-scale book review dataset that includes fine-grained spoiler annotations at the sentence-level, as well as book and (anonymized) user information. Second, we carefully an... | 89643a605576addc7aa22ab54ac22d7c | 2,019 | [
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ACL | LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding | Structured document understanding has attracted considerable attention and made significant progress recently, owing to its crucial role in intelligent document processing. However, most existing related models can only deal with the document data of specific language(s) (typically English) included in the pre-training... | d15b601a780eb9f813cf6f77c0f2afb0 | 2,022 | [
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ACL | A Probabilistic Generative Model for Typographical Analysis of Early Modern Printing | We propose a deep and interpretable probabilistic generative model to analyze glyph shapes in printed Early Modern documents. We focus on clustering extracted glyph images into underlying templates in the presence of multiple confounding sources of variance. Our approach introduces a neural editor model that first gene... | 6b2cfa98e113d16a8649f3c91af3d0b1 | 2,020 | [
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ACL | Syntactically Supervised Transformers for Faster Neural Machine Translation | Standard decoders for neural machine translation autoregressively generate a single target token per timestep, which slows inference especially for long outputs. While architectural advances such as the Transformer fully parallelize the decoder computations at training time, inference still proceeds sequentially. Recen... | d6837d774630a3b1d530edcafd5e17d2 | 2,019 | [
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ACL | Mitigating Gender Bias Amplification in Distribution by Posterior Regularization | Advanced machine learning techniques have boosted the performance of natural language processing. Nevertheless, recent studies, e.g., (CITATION) show that these techniques inadvertently capture the societal bias hidden in the corpus and further amplify it. However, their analysis is conducted only on models’ top predic... | e16829ae1de7a41c934805d3984582ba | 2,020 | [
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ACL | CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations | Supervised learning has traditionally focused on inductive learning by observing labeled examples of a task. In contrast, a hallmark of human intelligence is the ability to learn new concepts purely from language. Here, we explore training zero-shot classifiers for structured data purely from language. For this, we int... | a11a2a6f592ed9cd50fcdfa387c4f645 | 2,022 | [
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ACL | Training Neural Response Selection for Task-Oriented Dialogue Systems | Despite their popularity in the chatbot literature, retrieval-based models have had modest impact on task-oriented dialogue systems, with the main obstacle to their application being the low-data regime of most task-oriented dialogue tasks. Inspired by the recent success of pretraining in language modelling, we propose... | c404706489ca2f16f5a858742a8a4c04 | 2,019 | [
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ACL | End-to-End Modeling via Information Tree for One-Shot Natural Language Spatial Video Grounding | Natural language spatial video grounding aims to detect the relevant objects in video frames with descriptive sentences as the query. In spite of the great advances, most existing methods rely on dense video frame annotations, which require a tremendous amount of human effort. To achieve effective grounding under a lim... | a5f85eea4381fd71125b48bca5a93d74 | 2,022 | [
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ACL | Learning from Omission | Pragmatic reasoning allows humans to go beyond the literal meaning when interpret- ing language in context. Previous work has shown that such reasoning can improve the performance of already-trained language understanding systems. Here, we explore whether pragmatic reasoning during training can improve the quality of l... | c94f8d5703a282a7dbfab4aa41d98470 | 2,019 | [
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ACL | Designing Precise and Robust Dialogue Response Evaluators | Automatic dialogue response evaluator has been proposed as an alternative to automated metrics and human evaluation. However, existing automatic evaluators achieve only moderate correlation with human judgement and they are not robust. In this work, we propose to build a reference-free evaluator and exploit the power o... | ffcc6f3d3eb1f009b7d564ff4dd67b1f | 2,020 | [
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ACL | R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling | Human language understanding operates at multiple levels of granularity (e.g., words, phrases, and sentences) with increasing levels of abstraction that can be hierarchically combined. However, existing deep models with stacked layers do not explicitly model any sort of hierarchical process. In this paper, we propose a... | d47270b31b82fe740905cda46c16e25e | 2,021 | [
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ACL | Attention Is (not) All You Need for Commonsense Reasoning | The recently introduced BERT model exhibits strong performance on several language understanding benchmarks. In this paper, we describe a simple re-implementation of BERT for commonsense reasoning. We show that the attentions produced by BERT can be directly utilized for tasks such as the Pronoun Disambiguation Problem... | d64ef17eb0f4000b6cf2803af1d80fe3 | 2,019 | [
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ACL | Reducing Word Omission Errors in Neural Machine Translation: A Contrastive Learning Approach | While neural machine translation (NMT) has achieved remarkable success, NMT systems are prone to make word omission errors. In this work, we propose a contrastive learning approach to reducing word omission errors in NMT. The basic idea is to enable the NMT model to assign a higher probability to a ground-truth transla... | b4a543bc99d5f09afac73a6a3a300b72 | 2,019 | [
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ACL | Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward | Sequence-to-sequence models for abstractive summarization have been studied extensively, yet the generated summaries commonly suffer from fabricated content, and are often found to be near-extractive. We argue that, to address these issues, the summarizer should acquire semantic interpretation over input, e.g., via str... | 2d2d7cee9d6b4180fc2309ccf00f891a | 2,020 | [
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ACL | Dynamic Programming Encoding for Subword Segmentation in Neural Machine Translation | This paper introduces Dynamic Programming Encoding (DPE), a new segmentation algorithm for tokenizing sentences into subword units. We view the subword segmentation of output sentences as a latent variable that should be marginalized out for learning and inference. A mixed character-subword transformer is proposed, whi... | 4076d5a2c4252b156f73ce3e0c30c108 | 2,020 | [
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ACL | Are Prompt-based Models Clueless? | Finetuning large pre-trained language models with a task-specific head has advanced the state-of-the-art on many natural language understanding benchmarks. However, models with a task-specific head require a lot of training data, making them susceptible to learning and exploiting dataset-specific superficial cues that ... | f6715b828ab97b4539ac195b19de3286 | 2,022 | [
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ACL | MATINF: A Jointly Labeled Large-Scale Dataset for Classification, Question Answering and Summarization | Recently, large-scale datasets have vastly facilitated the development in nearly all domains of Natural Language Processing. However, there is currently no cross-task dataset in NLP, which hinders the development of multi-task learning. We propose MATINF, the first jointly labeled large-scale dataset for classification... | 28349b5e6e5fd0209712dbaa959b287e | 2,020 | [
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ACL | Learning to Ask Conversational Questions by Optimizing Levenshtein Distance | Conversational Question Simplification (CQS) aims to simplify self-contained questions into conversational ones by incorporating some conversational characteristics, e.g., anaphora and ellipsis. Existing maximum likelihood estimation based methods often get trapped in easily learned tokens as all tokens are treated equ... | 1ad39e439a8b0a255eddb8e14522eb42 | 2,021 | [
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ACL | Neural Generation of Dialogue Response Timings | The timings of spoken response offsets in human dialogue have been shown to vary based on contextual elements of the dialogue. We propose neural models that simulate the distributions of these response offsets, taking into account the response turn as well as the preceding turn. The models are designed to be integrated... | d85cfb7e1ac7461298dab43e9e3bb780 | 2,020 | [
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ACL | Analyzing Linguistic Differences between Owner and Staff Attributed Tweets | Research on social media has to date assumed that all posts from an account are authored by the same person. In this study, we challenge this assumption and study the linguistic differences between posts signed by the account owner or attributed to their staff. We introduce a novel data set of tweets posted by U.S. pol... | 2f45f62c4713278a4e19f4a782c0f246 | 2,019 | [
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ACL | Syntactic Data Augmentation Increases Robustness to Inference Heuristics | Pretrained neural models such as BERT, when fine-tuned to perform natural language inference (NLI), often show high accuracy on standard datasets, but display a surprising lack of sensitivity to word order on controlled challenge sets. We hypothesize that this issue is not primarily caused by the pretrained model’s lim... | 1a1157ae5c49602dc81ffd3f942f12f0 | 2,020 | [
"pretrained neural models such as bert , when fine - tuned to perform natural language inference ( nli ) , often show high accuracy on standard datasets , but display a surprising lack of sensitivity to word order on controlled challenge sets .",
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ACL | Domain Adaptive Inference for Neural Machine Translation | We investigate adaptive ensemble weighting for Neural Machine Translation, addressing the case of improving performance on a new and potentially unknown domain without sacrificing performance on the original domain. We adapt sequentially across two Spanish-English and three English-German tasks, comparing unregularized... | 98681c2ac1fdadc7bb9a49af2bc1e78c | 2,019 | [
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