context stringlengths 5k 202k | question stringlengths 17 163 | answer stringlengths 1 619 ⌀ | length int64 819 31.7k | dataset stringclasses 5
values | context_range stringclasses 5
values |
|---|---|---|---|---|---|
INTRODUCTION
The idea of language identification is to classify a given audio signal into a particular class using a classification algorithm. Commonly language identification task was done using i-vector systems [1]. A very well known approach for language identification proposed by N. Dahek et al. [1] uses the GMM-UB... | What is the GhostVLAD approach? | extension of the NetVLAD, adds Ghost clusters along with the NetVLAD clusters | 2,454 | qasper | 3k |
Introduction
Abusive language refers to any type of insult, vulgarity, or profanity that debases the target; it also can be anything that causes aggravation BIBREF0 , BIBREF1 . Abusive language is often reframed as, but not limited to, offensive language BIBREF2 , cyberbullying BIBREF3 , othering language BIBREF4 , and... | What additional features and context are proposed? | using tweets that one has replied or quoted to as contextual information | 2,060 | qasper | 3k |
Introduction
Language modelling in its inception had one-hot vector encoding of words. However, it captures only alphabetic ordering but not the word semantic similarity. Vector space models helps to learn word representations in a lower dimensional space and also captures semantic similarity. Learning word embedding a... | How does this approach compare to other WSD approaches employing word embeddings? | GM$\_$KL achieves better correlation than existing approaches for various metrics on SCWS dataset. | 2,189 | qasper | 3k |
Introduction
Text simplification aims to reduce the lexical and structural complexity of a text, while still retaining the semantic meaning, which can help children, non-native speakers, and people with cognitive disabilities, to understand text better. One of the methods of automatic text simplification can be general... | what language does this paper focus on? | English | 2,243 | qasper | 3k |
Introduction
There have been many implementations of the word2vec model in either of the two architectures it provides: continuous skipgram and CBoW (BIBREF0). Similar distributed models of word or subword embeddings (or vector representations) find usage in sota, deep neural networks like BERT and its successors (BIBR... | What sentiment analysis dataset is used? | IMDb dataset of movie reviews | 2,327 | qasper | 3k |
Introduction
Automatic classification of sentiment has mainly focused on categorizing tweets in either two (binary sentiment analysis) or three (ternary sentiment analysis) categories BIBREF0 . In this work we study the problem of fine-grained sentiment classification where tweets are classified according to a five-poi... | By how much did they improve? | They decrease MAE in 0.34 | 2,735 | qasper | 3k |
Introduction
This paper describes our approach and results for Task 2 of the CoNLL–SIGMORPHON 2018 shared task on universal morphological reinflection BIBREF0 . The task is to generate an inflected word form given its lemma and the context in which it occurs.
Morphological (re)inflection from context is of particular r... | What architecture does the encoder have? | LSTM | 2,289 | qasper | 3k |
Introduction
Conventional automatic speech recognition (ASR) systems typically consist of several independently learned components: an acoustic model to predict context-dependent sub-phoneme states (senones) from audio, a graph structure to map senones to phonemes, and a pronunciation model to map phonemes to words. Hy... | what were the baselines? | Unanswerable | 1,856 | qasper | 3k |
Introduction
In the kitchen, we increasingly rely on instructions from cooking websites: recipes. A cook with a predilection for Asian cuisine may wish to prepare chicken curry, but may not know all necessary ingredients apart from a few basics. These users with limited knowledge cannot rely on existing recipe generati... | What metrics are used for evaluation? | Byte-Pair Encoding perplexity (BPE PPL),
BLEU-1,
BLEU-4,
ROUGE-L,
percentage of distinct unigram (D-1),
percentage of distinct bigrams(D-2),
user matching accuracy(UMA),
Mean Reciprocal Rank(MRR)
Pairwise preference over baseline(PP) | 2,673 | qasper | 3k |
Introduction
Microblogging such as Twitter and Weibo is a popular social networking service, which allows users to post messages up to 140 characters. There are millions of active users on the platform who stay connected with friends. Unfortunately, spammers also use it as a tool to post malicious links, send unsolicit... | LDA is an unsupervised method; is this paper introducing an unsupervised approach to spam detection? | No | 2,239 | qasper | 3k |
Introduction
Accurate language identification (LID) is the first step in many natural language processing and machine comprehension pipelines. If the language of a piece of text is known then the appropriate downstream models like parts of speech taggers and language models can be applied as required.
LID is further al... | Which languages are similar to each other? | Nguni languages (zul, xho, nbl, ssw), Sotho languages (nso, sot, tsn) | 1,877 | qasper | 3k |
Introduction
Suppose a user wants to write a sentence “I will be 10 minutes late.” Ideally, she would type just a few keywords such as “10 minutes late” and an autocomplete system would be able to infer the intended sentence (Figure FIGREF1). Existing left-to-right autocomplete systems BIBREF0, BIBREF1 can often be ine... | How are models evaluated in this human-machine communication game? | by training an autocomplete system on 500K randomly sampled sentences from Yelp reviews | 1,873 | qasper | 3k |
Introduction
Performance appraisal (PA) is an important HR process, particularly for modern organizations that crucially depend on the skills and expertise of their workforce. The PA process enables an organization to periodically measure and evaluate every employee's performance. It also provides a mechanism to link t... | What evaluation metrics are looked at for classification tasks? | Precision, Recall, F-measure, accuracy | 3,044 | qasper | 3k |
Introduction
Deep Neural Networks (DNN) have been widely employed in industry for solving various Natural Language Processing (NLP) tasks, such as text classification, sequence labeling, question answering, etc. However, when engineers apply DNN models to address specific NLP tasks, they often face the following challe... | What neural network modules are included in NeuronBlocks? | Embedding Layer, Neural Network Layers, Loss Function, Metrics | 1,678 | qasper | 3k |
Introduction
The task of speculation detection and scope resolution is critical in distinguishing factual information from speculative information. This has multiple use-cases, like systems that determine the veracity of information, and those that involve requirement analysis. This task is particularly important to th... | What were the baselines? | varied from Maximum Entropy Classifiers (BIBREF4) to Support Vector Machines (BIBREF5,BIBREF6,BIBREF7,BIBREF8), Recursive Neural Networks (BIBREF9,BIBREF10), Convolutional Neural Networks (BIBREF11) and most recently transfer learning-based architectures like Bidirectional Encoder Representation from Transformers (BERT... | 2,215 | qasper | 3k |
Introduction
We understand from Zipf's Law that in any natural language corpus a majority of the vocabulary word types will either be absent or occur in low frequency. Estimating the statistical properties of these rare word types is naturally a difficult task. This is analogous to the curse of dimensionality when we d... | What other tasks do they test their method on? | null | 2,473 | qasper | 3k |
Introduction and Background
Task-oriented dialogue systems are primarily designed to search and interact with large databases which contain information pertaining to a certain dialogue domain: the main purpose of such systems is to assist the users in accomplishing a well-defined task such as flight booking BIBREF0, to... | Was PolyReponse evaluated against some baseline? | No | 2,738 | qasper | 3k |
Introduction
Blogging gained momentum in 1999 and became especially popular after the launch of freely available, hosted platforms such as blogger.com or livejournal.com. Blogging has progressively been used by individuals to share news, ideas, and information, but it has also developed a mainstream role to the extent ... | How do they obtain psychological dimensions of people? | using the Meaning Extraction Method | 1,440 | qasper | 3k |
Introduction
The automatic identification, extraction and representation of the information conveyed in texts is a key task nowadays. In fact, this research topic is increasing its relevance with the exponential growth of social networks and the need to have tools that are able to automatically process them BIBREF0.
So... | Were any of the pipeline components based on deep learning models? | No | 2,276 | qasper | 3k |
Introduction
End-to-end speech-to-text translation (ST) has attracted much attention recently BIBREF2, BIBREF3, BIBREF4, BIBREF5, BIBREF6 given its simplicity against cascading automatic speech recognition (ASR) and machine translation (MT) systems. The lack of labeled data, however, has become a major blocker for brid... | How is the quality of the data empirically evaluated? | Validated transcripts were sent to professional translators., various sanity checks to the translations, sanity check the overlaps of train, development and test sets | 2,435 | qasper | 3k |
Introduction
Text simplification aims to reduce the lexical and structural complexity of a text, while still retaining the semantic meaning, which can help children, non-native speakers, and people with cognitive disabilities, to understand text better. One of the methods of automatic text simplification can be general... | by how much did their model improve? | For the WikiLarge dataset, the improvement over baseline NMT is 2.11 BLEU, 1.7 FKGL and 1.07 SARI.
For the WikiSmall dataset, the improvement over baseline NMT is 8.37 BLEU. | 2,271 | qasper | 3k |
Introduction
In the age of information dissemination without quality control, it has enabled malicious users to spread misinformation via social media and aim individual users with propaganda campaigns to achieve political and financial gains as well as advance a specific agenda. Often disinformation is complied in the... | Which basic neural architecture perform best by itself? | BERT | 1,507 | qasper | 3k |
Introduction
Microblogging such as Twitter and Weibo is a popular social networking service, which allows users to post messages up to 140 characters. There are millions of active users on the platform who stay connected with friends. Unfortunately, spammers also use it as a tool to post malicious links, send unsolicit... | What is the benchmark dataset and is its quality high? | Social Honeypot dataset (public) and Weibo dataset (self-collected); yes | 2,242 | qasper | 3k |
Introduction
This paper describes our approach and results for Task 2 of the CoNLL–SIGMORPHON 2018 shared task on universal morphological reinflection BIBREF0 . The task is to generate an inflected word form given its lemma and the context in which it occurs.
Morphological (re)inflection from context is of particular r... | What architecture does the decoder have? | LSTM | 2,289 | qasper | 3k |
Introduction
In the age of information dissemination without quality control, it has enabled malicious users to spread misinformation via social media and aim individual users with propaganda campaigns to achieve political and financial gains as well as advance a specific agenda. Often disinformation is complied in the... | What is best performing model among author's submissions, what performance it had? | For SLC task, the "ltuorp" team has the best performing model (0.6323/0.6028/0.6649 for F1/P/R respectively) and for FLC task the "newspeak" team has the best performing model (0.2488/0.2863/0.2201 for F1/P/R respectively). | 1,541 | qasper | 3k |
Introduction
Deep Learning approaches have achieved impressive results on various NLP tasks BIBREF0 , BIBREF1 , BIBREF2 and have become the de facto approach for any NLP task. However, these deep learning techniques have found to be less effective for low-resource languages when the available training data is very less... | How do they match words before reordering them? | Unanswerable | 2,231 | qasper | 3k |
Introduction
The explosion of available scientific articles in the Biomedical domain has led to the rise of Biomedical Information Extraction (BioIE). BioIE systems aim to extract information from a wide spectrum of articles including medical literature, biological literature, electronic health records, etc. that can b... | Does the paper explore extraction from electronic health records? | Yes | 3,035 | qasper | 3k |
Introduction
Neural networks have been successfully used to describe images with text using sequence-to-sequence models BIBREF0. However, the results are simple and dry captions which are one or two phrases long. Humans looking at a painting see more than just objects. Paintings stimulate sentiments, metaphors and stor... | What models are used for painting embedding and what for language style transfer? | generating a poem from images we use an existing actor-critic architecture, various types of sequence to sequence models | 1,653 | qasper | 3k |
Introduction
Bidirectional Encoder Representations from Transformers (BERT) is a novel Transformer BIBREF0 model, which recently achieved state-of-the-art performance in several language understanding tasks, such as question answering, natural language inference, semantic similarity, sentiment analysis, and others BIBR... | On top of BERT does the RNN layer work better or the transformer layer? | Transformer over BERT (ToBERT) | 2,655 | qasper | 3k |
Introduction
Relation classification is the task of assigning sentences with two marked entities to a predefined set of relations. The sentence “We poured the <e1>milk</e1> into the <e2>pumpkin mixture</e2>.”, for example, expresses the relation Entity-Destination(e1,e2). While early research mostly focused on support ... | How do they obtain the new context represetation? | They use two independent convolutional and max-pooling layers on (1) a combination of the left context, the left entity and the middle context; and (2) a combination of the middle context, the right entity and the right context. They concatenated the two results after pooling to get the new context representation. | 2,435 | qasper | 3k |
Introduction
Named Entity Recognition (NER) is a foremost NLP task to label each atomic elements of a sentence into specific categories like "PERSON", "LOCATION", "ORGANIZATION" and othersBIBREF0. There has been an extensive NER research on English, German, Dutch and Spanish language BIBREF1, BIBREF2, BIBREF3, BIBREF4,... | How many different types of entities exist in the dataset? | OurNepali contains 3 different types of entities, ILPRL contains 4 different types of entities | 2,851 | qasper | 3k |
Data
We build and test our MMT models on the Multi30K dataset BIBREF21 . Each image in Multi30K contains one English (EN) description taken from Flickr30K BIBREF22 and human translations into German (DE), French (FR) and Czech BIBREF23 , BIBREF24 , BIBREF25 . The dataset contains 29,000 instances for training, 1,014 fo... | What dataset does this approach achieve state of the art results on? | the English-German dataset | 1,833 | qasper | 3k |
Introduction
As social media, specially Twitter, takes on an influential role in presidential elections in the U.S., natural language processing of political tweets BIBREF0 has the potential to help with nowcasting and forecasting of election results as well as identifying the main issues with a candidate – tasks of mu... | Which toolkits do they use? | BIBREF17, BIBREF18, TensiStrength BIBREF13, TwitterNLP BIBREF6, BIBREF19, CogComp-NLP BIBREF20, Stanford NLP NER BIBREF21 | 1,452 | qasper | 3k |
Background
Teaching machine to read and comprehend a given passage/paragraph and answer its corresponding questions is a challenging task. It is also one of the long-term goals of natural language understanding, and has important applications in e.g., building intelligent agents for conversation and customer service su... | Do they use attention? | Yes | 1,687 | qasper | 3k |
Introduction
Bidirectional Encoder Representations from Transformers (BERT) is a novel Transformer BIBREF0 model, which recently achieved state-of-the-art performance in several language understanding tasks, such as question answering, natural language inference, semantic similarity, sentiment analysis, and others BIBR... | What datasets did they use for evaluation? | CSAT dataset, 20 newsgroups, Fisher Phase 1 corpus | 2,652 | qasper | 3k |
Introduction
The recently introduced BERT model BIBREF0 exhibits strong performance on several language understanding benchmarks. To what extent does it capture syntax-sensitive structures?
Recent work examines the extent to which RNN-based models capture syntax-sensitive phenomena that are traditionally taken as evide... | Were any of these tasks evaluated in any previous work? | Yes | 1,464 | qasper | 3k |
Introduction
As social media, specially Twitter, takes on an influential role in presidential elections in the U.S., natural language processing of political tweets BIBREF0 has the potential to help with nowcasting and forecasting of election results as well as identifying the main issues with a candidate – tasks of mu... | Is datasets for sentiment analysis balanced? | No | 1,441 | qasper | 3k |
Introduction
Text simplification aims to reduce the lexical and structural complexity of a text, while still retaining the semantic meaning, which can help children, non-native speakers, and people with cognitive disabilities, to understand text better. One of the methods of automatic text simplification can be general... | what are the sizes of both datasets? | training set has 89,042 sentence pairs, and the test set has 100 pairs, training set contains 296,402, 2,000 for development and 359 for testing | 2,266 | qasper | 3k |
Introduction
Offensive content has become pervasive in social media and a reason of concern for government organizations, online communities, and social media platforms. One of the most common strategies to tackle the problem is to train systems capable of recognizing offensive content, which then can be deleted or set... | What models are used in the experiment? | linear SVM, bidirectional Long Short-Term-Memory (BiLSTM), Convolutional Neural Network (CNN) | 2,250 | qasper | 3k |
Introduction
From a group of small users at the time of its inception in 2009, Quora has evolved in the last few years into one of the largest community driven Q&A sites with diverse user communities. With the help of efficient content moderation/review policies and active in-house review team, efficient Quora bots, th... | Do the answered questions measure for the usefulness of the answer? | No | 1,561 | qasper | 3k |
Introduction
Twitter, a micro-blogging and social networking site has emerged as a platform where people express themselves and react to events in real-time. It is estimated that nearly 500 million tweets are sent per day . Twitter data is particularly interesting because of its peculiar nature where people convey mess... | what pretrained word embeddings were used? | Pretrained word embeddings were not used | 1,771 | qasper | 3k |
Introduction
In the kitchen, we increasingly rely on instructions from cooking websites: recipes. A cook with a predilection for Asian cuisine may wish to prepare chicken curry, but may not know all necessary ingredients apart from a few basics. These users with limited knowledge cannot rely on existing recipe generati... | What were their results on the new dataset? | average recipe-level coherence scores of 1.78-1.82, human evaluators preferred personalized model outputs to baseline 63% of the time | 2,666 | qasper | 3k |
Introduction
Neural networks have been successfully used to describe images with text using sequence-to-sequence models BIBREF0. However, the results are simple and dry captions which are one or two phrases long. Humans looking at a painting see more than just objects. Paintings stimulate sentiments, metaphors and stor... | What limitations do the authors demnostrate of their model? | Since we do not have an end-to-end dataset, the generated English poem may not work well with Shakespeare style transfer | 1,651 | qasper | 3k |
Introduction
Word Sense Disambiguation (WSD) is a fundamental task and long-standing challenge in Natural Language Processing (NLP), which aims to find the exact sense of an ambiguous word in a particular context BIBREF0. Previous WSD approaches can be grouped into two main categories: knowledge-based and supervised me... | Is SemCor3.0 reflective of English language data in general? | Yes | 2,000 | qasper | 3k |
Introduction
End-to-end speech-to-text translation (ST) has attracted much attention recently BIBREF2, BIBREF3, BIBREF4, BIBREF5, BIBREF6 given its simplicity against cascading automatic speech recognition (ASR) and machine translation (MT) systems. The lack of labeled data, however, has become a major blocker for brid... | How big is Augmented LibriSpeech dataset? | Unanswerable | 2,410 | qasper | 3k |
Introduction
Automatic classification of sentiment has mainly focused on categorizing tweets in either two (binary sentiment analysis) or three (ternary sentiment analysis) categories BIBREF0 . In this work we study the problem of fine-grained sentiment classification where tweets are classified according to a five-poi... | What dataset did they use? | high-quality datasets from SemEval-2016 “Sentiment Analysis in Twitter” task | 2,738 | qasper | 3k |
Introduction
Word Sense Disambiguation (WSD) is a fundamental task and long-standing challenge in Natural Language Processing (NLP), which aims to find the exact sense of an ambiguous word in a particular context BIBREF0. Previous WSD approaches can be grouped into two main categories: knowledge-based and supervised me... | Do they use large or small BERT? | small BERT | 1,999 | qasper | 3k |
Introduction
There exists a class of language construction known as pun in natural language texts and utterances, where a certain word or other lexical items are used to exploit two or more separate meanings. It has been shown that understanding of puns is an important research question with various real-world applicat... | What is the tagging scheme employed? | A new tagging scheme that tags the words before and after the pun as well as the pun words. | 2,974 | qasper | 3k |
Introduction
End-to-end speech-to-text translation (ST) has attracted much attention recently BIBREF2, BIBREF3, BIBREF4, BIBREF5, BIBREF6 given its simplicity against cascading automatic speech recognition (ASR) and machine translation (MT) systems. The lack of labeled data, however, has become a major blocker for brid... | Is Arabic one of the 11 languages in CoVost? | No | 2,413 | qasper | 3k |
Introduction
Modelling the relationship between sequences is extremely significant in most retrieval or classification problems involving two sequences. Traditionally, in Siamese networks, Hadamard product or concatenation have been used to fuse two vector representations of two input sequences to form a final represen... | On which tasks do they test their conflict method? | Task 1: Quora Duplicate Question Pair Detection, Task 2: Ranking questions | 2,577 | qasper | 3k |
Introduction
In the kitchen, we increasingly rely on instructions from cooking websites: recipes. A cook with a predilection for Asian cuisine may wish to prepare chicken curry, but may not know all necessary ingredients apart from a few basics. These users with limited knowledge cannot rely on existing recipe generati... | What are the baseline models? | name-based Nearest-Neighbor model (NN), Encoder-Decoder baseline with ingredient attention (Enc-Dec) | 2,655 | qasper | 3k |
Introduction
The Flickr30K dataset BIBREF0 is a collection of over 30,000 images with 5 crowdsourced descriptions each. It is commonly used to train and evaluate neural network models that generate image descriptions (e.g. BIBREF2 ). An untested assumption behind the dataset is that the descriptions are based on the im... | Which methods are considered to find examples of biases and unwarranted inferences?? | spot patterns by just looking at a collection of images, tag all descriptions with part-of-speech information, I applied Louvain clustering | 2,204 | qasper | 3k |
Winograd Schemas
A Winograd schema (Levesque, Davis, and Morgenstern 2012) is a pair of sentences, or of short texts, called the elements of the schema, that satisfy the following constraints:
The following is an example of a Winograd schema:
Here, the two sentences differ only in the last word: `large' vs. `small'. Th... | What language do they explore? | English, French, German | 2,285 | qasper | 3k |
Introduction
Performance appraisal (PA) is an important HR process, particularly for modern organizations that crucially depend on the skills and expertise of their workforce. The PA process enables an organization to periodically measure and evaluate every employee's performance. It also provides a mechanism to link t... | What summarization algorithms did the authors experiment with? | LSA, TextRank, LexRank and ILP-based summary. | 3,045 | qasper | 3k |
Introduction
Natural languages evolve and words have always been subject to semantic change over time BIBREF1. With the rise of large digitized text resources recent NLP technologies have made it possible to capture such change with vector space models BIBREF2, BIBREF3, BIBREF4, BIBREF5, topic models BIBREF6, BIBREF7, ... | What is the corpus used for the task? | DTA18, DTA19 | 1,908 | qasper | 3k |
INTRODUCTION
The idea of language identification is to classify a given audio signal into a particular class using a classification algorithm. Commonly language identification task was done using i-vector systems [1]. A very well known approach for language identification proposed by N. Dahek et al. [1] uses the GMM-UB... | Which 7 Indian languages do they experiment with? | Hindi, English, Kannada, Telugu, Assamese, Bengali and Malayalam | 2,453 | qasper | 3k |
Introduction
Reading Comprehension (RC) has become a central task in natural language processing, with great practical value in various industries. In recent years, many large-scale RC datasets in English BIBREF0, BIBREF1, BIBREF2, BIBREF3, BIBREF4, BIBREF5, BIBREF6 have nourished the development of numerous powerful a... | What is the model performance on target language reading comprehension? | Table TABREF6, Table TABREF8 | 2,492 | qasper | 3k |
Introduction
Named Entity Recognition (NER) is a foremost NLP task to label each atomic elements of a sentence into specific categories like "PERSON", "LOCATION", "ORGANIZATION" and othersBIBREF0. There has been an extensive NER research on English, German, Dutch and Spanish language BIBREF1, BIBREF2, BIBREF3, BIBREF4,... | What is the size of the dataset? | Dataset contains 3606 total sentences and 79087 total entities. | 2,843 | qasper | 3k |
Introduction
The cognitive processes involved in human language comprehension are complex and only partially identified. According to the dual-stream model of speech comprehension BIBREF1 , sound waves are first converted to phoneme-like features and further processed by a ventral stream that maps those features onto w... | What datasets are used? | Answer with content missing: (Whole Method and Results sections) The primary dataset we use is the ERP data collected and computed by Frank et al. (2015), and we also use behavioral data (eye-tracking data and self-paced reading times) from Frank et al. (2013) which were collected on the same set of 205 sentences.
Sele... | 1,971 | qasper | 3k |
Introduction
Decoding intended speech or motor activity from brain signals is one of the major research areas in Brain Computer Interface (BCI) systems BIBREF0 , BIBREF1 . In particular, speech-related BCI technologies attempt to provide effective vocal communication strategies for controlling external devices through ... | What data was presented to the subjects to elicit event-related responses? | 7 phonemic/syllabic ( /iy/, /piy/, /tiy/, /diy/, /uw/, /m/, /n/ ) as well as 4 words(pat, pot, knew and gnaw) | 2,379 | qasper | 3k |
Introduction
Abusive language refers to any type of insult, vulgarity, or profanity that debases the target; it also can be anything that causes aggravation BIBREF0 , BIBREF1 . Abusive language is often reframed as, but not limited to, offensive language BIBREF2 , cyberbullying BIBREF3 , othering language BIBREF4 , and... | What learning models are used on the dataset? | Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), Random Forests (RF), Gradient Boosted Trees (GBT), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) | 2,074 | qasper | 3k |
Introduction
Pre-training of language models has been shown to provide large improvements for a range of language understanding tasks BIBREF0 , BIBREF1 , BIBREF2 , BIBREF3 . The key idea is to train a large generative model on vast corpora and use the resulting representations on tasks for which only limited amounts of... | What language model architectures are used? | uni-directional model to augment the decoder | 1,914 | qasper | 3k |
Introduction and Background
Many reinforcement learning algorithms are designed for relatively small discrete or continuous action spaces and so have trouble scaling. Text-adventure games—or interaction fictions—are simulations in which both an agents' state and action spaces are in textual natural language. An example... | What are the results from these proposed strategies? | Reward of 11.8 for the A2C-chained model, 41.8 for the KG-A2C-chained model, 40 for A2C-Explore and 44 for KG-A2C-Explore. | 2,443 | qasper | 3k |
Introduction
Recent years have seen unprecedented progress for Natural Language Processing (NLP) on almost every NLP subtask. Even though low-resource settings have also been explored, this progress has overwhelmingly been observed in languages with significant data resources that can be leveraged to train deep neural ... | How is non-standard pronunciation identified? | Unanswerable | 3,018 | qasper | 3k |
Introduction
Part-of-speech tagging is now a classic task in natural language processing, for which many systems have been developed or adapted for a large variety of languages. Its aim is to associate each “word” with a morphosyntactic tag, whose granularity can range from a simple morphosyntactic category, or part-of... | which languages are explored? | Bulgarian, Croatian, Czech, Danish, English, French, German, Indonesian, Italian, Norwegian, Persian, Polish, Portuguese, Slovenian, Spanish and Swedish | 2,697 | qasper | 3k |
Introduction
Writing errors can occur in many different forms – from relatively simple punctuation and determiner errors, to mistakes including word tense and form, incorrect collocations and erroneous idioms. Automatically identifying all of these errors is a challenging task, especially as the amount of available ann... | What was the baseline used? | error detection system by Rei2016 | 2,132 | qasper | 3k |
Introduction
Twitter is a widely used microblogging platform, where users post and interact with messages, “tweets”. Understanding the semantic representation of tweets can benefit a plethora of applications such as sentiment analysis BIBREF0 , BIBREF1 , hashtag prediction BIBREF2 , paraphrase detection BIBREF3 and mic... | Which dataset do they use? | Unanswerable | 1,902 | qasper | 3k |
Introduction
Cancer is one of the leading causes of death in the world, with over 80,000 deaths registered in Canada in 2017 (Canadian Cancer Statistics 2017). A computer-aided system for cancer diagnosis usually involves a pathologist rendering a descriptive report after examining the tissue glass slides obtained from... | What features are used? | Unanswerable | 2,108 | qasper | 3k |
Introduction
In recent years, there has been a movement to leverage social medial data to detect, estimate, and track the change in prevalence of disease. For example, eating disorders in Spanish language Twitter tweets BIBREF0 and influenza surveillance BIBREF1 . More recently, social media has been leveraged to monit... | How is the dataset annotated? | no evidence of depression, depressed mood, disturbed sleep, fatigue or loss of energy | 1,947 | qasper | 3k |
Introduction
Pretrained Language Models (PTLMs) such as BERT BIBREF1 have spearheaded advances on many NLP tasks. Usually, PTLMs are pretrained on unlabeled general-domain and/or mixed-domain text, such as Wikipedia, digital books or the Common Crawl corpus.
When applying PTLMs to specific domains, it can be useful to ... | Which eight NER tasks did they evaluate on? | BC5CDR-disease, NCBI-disease, BC5CDR-chem, BC4CHEMD, BC2GM, JNLPBA, LINNAEUS, Species-800 | 2,800 | qasper | 3k |
Introduction
Understanding the emotions expressed in a text or message is of high relevance nowadays. Companies are interested in this to get an understanding of the sentiment of their current customers regarding their products and the sentiment of their potential customers to attract new ones. Moreover, changes in a p... | How was the training data translated? | using the machine translation platform Apertium | 2,423 | qasper | 3k |
Introduction
Propaganda aims at influencing people's mindset with the purpose of advancing a specific agenda. In the Internet era, thanks to the mechanism of sharing in social networks, propaganda campaigns have the potential of reaching very large audiences BIBREF0, BIBREF1, BIBREF2.
Propagandist news articles use spe... | What was the baseline for this task? | The baseline system for the SLC task is a very simple logistic regression classifier with default parameters. The baseline for the FLC task generates spans and selects one of the 18 techniques randomly. | 3,001 | qasper | 3k |
Introduction
There exists a class of language construction known as pun in natural language texts and utterances, where a certain word or other lexical items are used to exploit two or more separate meanings. It has been shown that understanding of puns is an important research question with various real-world applicat... | What baselines do they compare with? | They compare with the following models: by Pedersen (2017), by Pramanick and Das (2017), by Mikhalkova and Karyakin (2017), by Vadehra (2017), Indurthi and Oota (2017), by Vechtomova (2017), by (Cai et al., 2018), and CRF. | 2,991 | qasper | 3k |
Introduction
Offensive content has become pervasive in social media and a reason of concern for government organizations, online communities, and social media platforms. One of the most common strategies to tackle the problem is to train systems capable of recognizing offensive content, which then can be deleted or set... | In what language are the tweets? | English | 2,240 | qasper | 3k |
Introduction
Grammar induction is the task of inducing hierarchical syntactic structure from data. Statistical approaches to grammar induction require specifying a probabilistic grammar (e.g. formalism, number and shape of rules), and fitting its parameters through optimization. Early work found that it was difficult t... | which chinese datasets were used? | Answer with content missing: (Data section) Chinese with version 5.1 of the Chinese Penn Treebank (CTB) | 2,545 | qasper | 3k |
Introduction
Question answering (QA) has been a blooming research field for the last decade. Selection-based QA implies a family of tasks that find answer contexts from large data given questions in natural language. Three tasks have been proposed for selection-based QA. Given a document, answer extraction BIBREF0 , BI... | Do they employ their indexing-based method to create a sample of a QA Wikipedia dataset? | Yes | 1,910 | qasper | 3k |
Introduction
Stance detection (also called stance identification or stance classification) is one of the considerably recent research topics in natural language processing (NLP). It is usually defined as a classification problem where for a text and target pair, the stance of the author of the text for that target is e... | Which sports clubs are the targets? | Galatasaray, Fenerbahçe | 2,234 | qasper | 3k |
Introduction
Many research attempts have proposed novel features that improve the performance of learning algorithms in particular tasks. Such features are often motivated by domain knowledge or manual labor. Although useful and often state-of-the-art, adapting such solutions on NLP systems across tasks can be tricky a... | Which hyperparameters were varied in the experiments on the four tasks? | number of clusters, seed value in clustering, selection of word vectors, window size and dimension of embedding | 2,753 | qasper | 3k |
Introduction
Understanding the emotions expressed in a text or message is of high relevance nowadays. Companies are interested in this to get an understanding of the sentiment of their current customers regarding their products and the sentiment of their potential customers to attract new ones. Moreover, changes in a p... | What were the scores of their system? | column Ens Test in Table TABREF19 | 2,424 | qasper | 3k |
Introduction
The automatic processing of medical texts and documents plays an increasingly important role in the recent development of the digital health area. To enable dedicated Natural Language Processing (NLP) that is highly accurate with respect to medically relevant categories, manually annotated data from this d... | How large is the corpus? | 8,275 sentences and 167,739 words in total | 2,669 | qasper | 3k |
Introduction
Deep learning systems have shown a lot of promise for extractive Question Answering (QA), with performance comparable to humans when large scale data is available. However, practitioners looking to build QA systems for specific applications may not have the resources to collect tens of thousands of questio... | Is it possible to convert a cloze-style questions to a naturally-looking questions? | Unanswerable | 2,764 | qasper | 3k |
Introduction
Named Entity Recognition (NER) is a foremost NLP task to label each atomic elements of a sentence into specific categories like "PERSON", "LOCATION", "ORGANIZATION" and othersBIBREF0. There has been an extensive NER research on English, German, Dutch and Spanish language BIBREF1, BIBREF2, BIBREF3, BIBREF4,... | How many sentences does the dataset contain? | 3606 | 2,835 | qasper | 3k |
Introduction
Deep neural networks (DNNs), in particular convolutional and recurrent neural networks, with huge architectures have been proven successful in wide range of tasks including audio processing such as speech to text [1 - 4], emotion recognition [5 - 8], speech/non-speech (e.g., of non-speech include noise, mu... | Which models/frameworks do they compare to? | MLP | 2,474 | qasper | 3k |
Introduction
Deep Neural Networks (DNN) have been widely employed in industry for solving various Natural Language Processing (NLP) tasks, such as text classification, sequence labeling, question answering, etc. However, when engineers apply DNN models to address specific NLP tasks, they often face the following challe... | How do the authors evidence the claim that many engineers find it a big overhead to choose from multiple frameworks, models and optimization techniques? | By conducting a survey among engineers | 1,692 | qasper | 3k |
Football Club Urartu (, translated Futbolayin Akumb Urartu), commonly known as Urartu, is an Armenian professional football team based in the capital Yerevan that currently plays in the Armenian Premier League. The club won the Armenian Cup three times, in 1992, 2007 and 2016. In 2013–2014, they won the Armenian Premie... | What is the name of the most active fan club? | South West Ultras fan club. | 819 | multifieldqa_en | 3k |
Hugh Hilton Goodwin (December 21, 1900 – February 25, 1980) was a decorated officer in the United States Navy with the rank of Vice Admiral. A veteran of both World Wars, he commanded escort carrier during the Mariana Islands campaign. Goodwin then served consecutively as Chief of Staff, Carrier Strike Group 6 and as ... | What was Hugh H. Goodwin's rank in the United States Navy? | Vice Admiral. | 2,292 | multifieldqa_en | 3k |
The 1951 Ohio State Buckeyes baseball team represented the Ohio State University in the 1951 NCAA baseball season. The head coach was Marty Karow, serving his 1st year.
The Buckeyes lost in the College World Series, defeated by the Texas A&M Aggies.
Roster
Schedule
! style="" | Regular Season
|- valign="top"
|- ... | What was the Buckeyes' record in their first game of the season? | They won their first game with a score of 15-3. | 972 | multifieldqa_en | 3k |
Brooksley Elizabeth Born (born August 27, 1940) is an American attorney and former public official who, from August 26, 1996, to June 1, 1999, was chair of the Commodity Futures Trading Commission (CFTC), the federal agency which oversees the U.S. futures and commodity options markets. During her tenure on the CFTC, Bo... | Who was Brooksley Elizabeth's first husband? | Jacob C. Landau. | 2,085 | multifieldqa_en | 3k |
Margaret Way (b. Brisbane d. Cleveland, Queensland, Australia ) was an Australian writer of romance novels and women's fiction. A prolific author, Way wrote more than 120 novels since 1970, many through Mills & Boon, a romance imprint of British publisher Harlequin UK Ltd., owned by Harlequin Enterprises.
Biography
Be... | Where was Margaret Way born and where did she die? | Margaret Way was born in Brisbane and died in Cleveland, Queensland, Australia. | 1,203 | multifieldqa_en | 3k |
Paper Info
Title: Is In-hospital Meta-information Useful for Abstractive Discharge Summary Generation?
Publish Date: 10 Mar 2023
Author List: Mamoru Komachi (from Tokyo Metropolitan University), Takashi Okumura (from Kitami Institute of Technology), Hiromasa Horiguchi (from National Hospital Organization), Yuji Matsum... | What is the future direction mentioned in the conclusion? | Verifying other meta-information such as patient's gender, age, race, etc. | 2,947 | multifieldqa_en | 3k |
\section{Introduction}
\label{sec:introduction}
Probabilistic models have proven to be very useful in a lot of applications in signal processing where signal estimation is needed \cite{rabiner1989tutorial,arulampalam2002tutorial,ji2008bayesian}. Some of their advantages are that 1) they force the designer to specify a... | What types of data did the authors use in their experiments? | The authors used simulated data and real data from a wireless MISO channel. | 2,554 | multifieldqa_en | 3k |
\section{INTRODUCTION}
The Tevatron Collider Run II started in March 2002 and is expected
to continue until the end of this decade. The Tevatron and the
two detectors, CDF and D\O, have been performing well in 2004,
each experiment is collecting data at the rate
of $\approx$10 pb$^{-1}$ per week.
The total luminosi... | When did the Tevatron Collider Run II start and when is it expected to end? | The Tevatron Collider Run II started in March 2002 and is expected to continue until the end of this decade. | 2,431 | multifieldqa_en | 3k |
Weep Not, Child is a 1964 novel by Kenyan author Ngũgĩ wa Thiong'o. It was his first novel, published in 1964 under the name James Ngugi. It was among the African Writers Series. It was the first English language|English novel to be published by an East African. Thiong'o's works deal with the relationship between Afric... | How many brother does Njoroge have? | Four. | 1,414 | multifieldqa_en | 3k |
\section{Introduction}\label{S1}
The multiple access interferences (MAI) is the root of user
limitation in CDMA systems \cite{R1,R3}. The parallel least mean
square-partial parallel interference cancelation (PLMS-PPIC) method
is a multiuser detector for code division multiple access (CDMA)
receivers which reduces the ... | What algorithm is engaged in the PLMS-PPIC method? | The normalized least mean square (NLMS) algorithm. | 2,008 | multifieldqa_en | 3k |
\section{Introduction}
Spectral line surveys have revealed that high-mass star-forming
regions are rich reservoirs of molecules from simple diatomic species
to complex and larger molecules (e.g.,
\citealt{schilke1997b,hatchell1998b,comito2005,bisschop2007}).
However, there have been rarely studies undertaken to invest... | What molecule was the focus of the study? | The focus of the study was on the reactive radical ethynyl (C$_2$H). | 2,115 | multifieldqa_en | 3k |
Weep Not, Child is a 1964 novel by Kenyan author Ngũgĩ wa Thiong'o. It was his first novel, published in 1964 under the name James Ngugi. It was among the African Writers Series. It was the first English language|English novel to be published by an East African. Thiong'o's works deal with the relationship between Afric... | When was Weep Not, Child first published? | Weep Not, Child was first published in 1964. | 1,489 | multifieldqa_en | 3k |
\section{Model equations} \label{sec:equations}
In drift-fluid models the continuity equation
\begin{align}
\frac{\partial n}{\partial t} + \nabla\cdot\left( n \vec u_E \right) &= 0 \label{eq:generala}
\end{align}
describes the dynamics of the electron density $n$. Here
$\vec u_E := (\hat{\vec b} \times \nabla \phi... | What is the relationship between the maximum velocity and the amplitude of the blob or depletion? | The maximum velocity scales with the square root of the amplitude. | 2,748 | multifieldqa_en | 3k |
Hugh Hilton Goodwin (December 21, 1900 – February 25, 1980) was a decorated officer in the United States Navy with the rank of Vice Admiral. A veteran of both World Wars, he commanded escort carrier during the Mariana Islands campaign. Goodwin then served consecutively as Chief of Staff, Carrier Strike Group 6 and as ... | When did Goodwin become a Naval aviator? | Goodwin became a Naval aviator in January 1929. | 2,294 | multifieldqa_en | 3k |
'无锡速芯微电子有限公司是一家集芯片 研发，销售和服务于一体的国家高新技 术企业，为客户提供高性能，高集成 度，极致体验的全协议快充芯片。 无锡速芯微电子有限公司 FastSOC Microelectronics Co.,Ltd. 销售联系方式： 联系人：顾先生 手机：1800 185 3071 邮箱：gpp@fastsoc.com 网址：www.fastsoc.com 地址：无锡市新吴区菱湖大道200号中国物联网国际创新园E-503室 顾工微信号 速芯微公众号 免责声明：本文所述方法、方案均供客户参考，用于提示或者展示芯片应用的一种或者多种方式，不作为最终产品的实际方案。文中所描述的功能和性能指标在实 验室环境下测试得到，部分可以... | 对于PD3.0协议，FS312BH支持的最高诱骗电压是多少？ | 48V. | 898 | multifieldqa_en | 3k |
Brooksley Elizabeth Born (born August 27, 1940) is an American attorney and former public official who, from August 26, 1996, to June 1, 1999, was chair of the Commodity Futures Trading Commission (CFTC), the federal agency which oversees the U.S. futures and commodity options markets. During her tenure on the CFTC, Bo... | When did Born resign as chairperson of the CFTC? | June 1, 1999. | 2,088 | multifieldqa_en | 3k |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.