Split (3)

train · 937 rows

id stringclasses 179 values	question stringlengths 8.75k 85.9k	answer dict
1909.00694	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What is the seed lexicon? Context: <<<Title>>> Minimally Supervised Learning of Affective Events Using Discourse Relations <<<Abstract>>> Recognizing affective events that trigger positive ...	{ "references": [ "seed lexicon consists of positive and negative predicates" ], "type": "extractive" }
1909.00694	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are labels available in dataset for supervision? Context: <<<Title>>> Minimally Supervised Learning of Affective Events Using Discourse Relations <<<Abstract>>> Recognizing affective e...	{ "references": [ "negative,positive" ], "type": "extractive" }
1909.00694	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How large is raw corpus used for training? Context: <<<Title>>> Minimally Supervised Learning of Affective Events Using Discourse Relations <<<Abstract>>> Recognizing affective events that ...	{ "references": [ "100 million sentences" ], "type": "extractive" }
1910.14497	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How is embedding quality assessed? Context: <<<Title>>> Probabilistic Bias Mitigation in Word Embeddings <<<Abstract>>> It has been shown that word embeddings derived from large corpora ten...	{ "references": [ "We compare this method of bias mitigation with the no bias mitigation (\"Orig\"), geometric bias mitigation (\"Geo\"), the two pieces of our method alone (\"Prob\" and \"KNN\") and the composite method (\"KNN+Prob\"). We note that the composite method performs reasonably well according the the ...
1912.02481	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What turn out to be more important high volume or high quality data? Context: <<<Title>>> Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yor\`ub\'a and Twi <<<...	{ "references": [ "only high-quality data helps", "high-quality" ], "type": "extractive" }
1912.02481	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What two architectures are used? Context: <<<Title>>> Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yor\`ub\'a and Twi <<<Abstract>>> The success of several a...	{ "references": [ "fastText,CWE-LP" ], "type": "extractive" }
2002.02224	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How is quality of the citation measured? Context: <<<Title>>> Citation Data of Czech Apex Courts <<<Abstract>>> In this paper, we introduce the citation data of the Czech apex courts (Supre...	{ "references": [ "it is necessary to evaluate the performance of the above mentioned part of the pipeline before proceeding further. The evaluation of the performance is summarised in Table TABREF11. It shows that organising the two models into the pipeline boosted the performance of the reference recognition mo...
2003.06651	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Is the method described in this work a clustering-based method? Context: <<<Title>>> Word Sense Disambiguation for 158 Languages using Word Embeddings Only <...	{ "references": [ "Yes" ], "type": "boolean" }
2003.06651	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How are the different senses annotated/labeled? Context: <<<Title>>> Word Sense Disambiguation for 158 Languages using Word Embeddings Only <<<Abstract>>> Disambiguation of word senses in ...	{ "references": [ "The contexts are manually labelled with WordNet senses of the target words" ], "type": "extractive" }
2003.06651	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Was any extrinsic evaluation carried out? Context: <<<Title>>> Word Sense Disambiguation for 158 Languages using Word Embeddings Only <<<Abstract>>> Disambig...	{ "references": [ "Yes" ], "type": "boolean" }
1910.04269	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Does the model use both spectrogram images and raw waveforms as features? Context: <<<Title>>> Spoken Language Identification using ConvNets <<<Abstract>>> L...	{ "references": [ "No" ], "type": "boolean" }
2001.00137	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Do they report results only on English datasets? Context: <<<Title>>> Stacked DeBERT: All Attention in Incomplete Data for Text Classification <<<Abstract>>>...	{ "references": [ "Yes" ], "type": "boolean" }
2001.00137	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Do they test their approach on a dataset without incomplete data? Context: <<<Title>>> Stacked DeBERT: All Attention in Incomplete Data for Text Classificati...	{ "references": [ "No" ], "type": "boolean" }
2001.00137	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Should their approach be applied only when dealing with incomplete data? Context: <<<Title>>> Stacked DeBERT: All Attention in Incomplete Data for Text Class...	{ "references": [ "No" ], "type": "boolean" }
2003.08529	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Did they propose other metrics? Context: <<<Title>>> Diversity, Density, and Homogeneity: Quantitative Characteristic Metrics for Text Collections <<<Abstrac...	{ "references": [ "Yes" ], "type": "boolean" }
2003.08529	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Which real-world datasets did they use? Context: <<<Title>>> Diversity, Density, and Homogeneity: Quantitative Characteristic Metrics for Text Collections <<<Abstract>>> Summarizing data sa...	{ "references": [ "SST-2 (Stanford Sentiment Treebank, version 2),Snips", "SST-2,Snips" ], "type": "extractive" }
2003.08553	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What experiments do the authors present to validate their system? Context: <<<Title>>> QnAMaker: Data to Bot in 2 Minutes <<<Abstract>>> Having a bot for seamless conversations is a much-de...	{ "references": [ " we measure our system's performance for datasets across various domains,evaluations are done by managed judges who understands the knowledge base and then judge user queries relevance to the QA pairs" ], "type": "extractive" }
2003.08553	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What components is the QnAMaker composed of? Context: <<<Title>>> QnAMaker: Data to Bot in 2 Minutes <<<Abstract>>> Having a bot for seamless conversations is a much-desired feature that pr...	{ "references": [ "QnAMaker Portal,QnaMaker Management APIs,Azure Search Index,QnaMaker WebApp,Bot", "QnAMaker Portal,QnaMaker Management APIs,Azure Search Index,QnaMaker WebApp,Bot" ], "type": "extractive" }
1909.12140	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Is the semantic hierarchy representation used for any task? Context: <<<Title>>> DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English...	{ "references": [ "Yes" ], "type": "boolean" }
1909.12140	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are the corpora used for the task? Context: <<<Title>>> DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English and German <<<Abstract>>> We introduce DisSim, a di...	{ "references": [ "For the English version, we performed both a thorough manual analysis and automatic evaluation across three commonly used TS datasets from two different domains,The evaluation of the German version is in progress." ], "type": "extractive" }
2002.11893	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How was the dataset collected? Context: <<<Title>>> CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset <<<Abstract>>> To advance multi-domain (cross-domain) dialogu...	{ "references": [ "Database Construction: we crawled travel information in Beijing from the Web, including Hotel, Attraction, and Restaurant domains (hereafter we name the three domains as HAR domains). Then, we used the metro information of entities in HAR domains to build the metro database. ,Goal Generation: a...
2002.11893	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are the benchmark models? Context: <<<Title>>> CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset <<<Abstract>>> To advance multi-domain (cross-domain) dialogu...	{ "references": [ "BERTNLU from ConvLab-2,a rule-based model (RuleDST) ,TRADE (Transferable Dialogue State Generator) ,a vanilla policy trained in a supervised fashion from ConvLab-2 (SL policy)" ], "type": "extractive" }
2002.11893	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How was the corpus annotated? Context: <<<Title>>> CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset <<<Abstract>>> To advance multi-domain (cross-domain) dialogue...	{ "references": [ "The workers were also asked to annotate both user states and system states,we used some rules to automatically annotate dialogue acts according to user states, system states, and dialogue histories" ], "type": "extractive" }
1909.02764	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Does the paper evaluate any adjustment to improve the predicion accuracy of face and audio features? Context: <<<Title>>> Towards Multimodal Emotion Recognit...	{ "references": [ "No" ], "type": "boolean" }
1909.02764	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How is face and audio data analysis evaluated? Context: <<<Title>>> Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning <<<Abstract>>> The recogni...	{ "references": [ "confusion matrices,$\\text{F}_1$ score" ], "type": "extractive" }
1909.02764	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are the emotion detection tools used for audio and face input? Context: <<<Title>>> Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning <<<Ab...	{ "references": [ "We apply an off-the-shelf tool for emotion recognition (the manufacturer cannot be disclosed due to licensing restrictions)", "cannot be disclosed due to licensing restrictions" ], "type": "extractive" }
1912.01252	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are the causal mapping methods employed? Context: <<<Title>>> Facilitating on-line opinion dynamics by mining expressions of causation. The case of climate change debates on The Guardi...	{ "references": [ "Axelrod's causal mapping method" ], "type": "extractive" }
1909.00578	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What dataset do they use? Context: <<<Title>>> SUM-QE: a BERT-based Summary Quality Estimation Model <<<Abstract>>> We propose SumQE, a novel Quality Estimation model for summarization base...	{ "references": [ "datasets from the NIST DUC-05, DUC-06 and DUC-07 shared tasks" ], "type": "extractive" }
1909.00578	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What simpler models do they look at? Context: <<<Title>>> SUM-QE: a BERT-based Summary Quality Estimation Model <<<Abstract>>> We propose SumQE, a novel Quality Estimation model for summari...	{ "references": [ "BiGRU s with attention,ROUGE,Language model (LM),Next sentence prediction" ], "type": "extractive" }
1910.11471	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What additional techniques are incorporated? Context: <<<Title>>> Machine Translation from Natural Language to Code using Long-Short Term Memory <<<Abstract>>> Making computer programming l...	{ "references": [ "incorporating coding syntax tree model" ], "type": "extractive" }
1910.11471	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What dataset do they use? Context: <<<Title>>> Machine Translation from Natural Language to Code using Long-Short Term Memory <<<Abstract>>> Making computer programming language more unders...	{ "references": [ " text-code parallel corpus" ], "type": "extractive" }
1910.11471	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Do they compare to other models? Context: <<<Title>>> Machine Translation from Natural Language to Code using Long-Short Term Memory <<<Abstract>>> Making co...	{ "references": [ "No" ], "type": "boolean" }
1910.11471	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What is the architecture of the system? Context: <<<Title>>> Machine Translation from Natural Language to Code using Long-Short Term Memory <<<Abstract>>> Making computer programming langua...	{ "references": [ "seq2seq translation" ], "type": "extractive" }
1910.11471	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What additional techniques could be incorporated to further improve accuracy? Context: <<<Title>>> Machine Translation from Natural Language to Code using Long-Short Term Memory <<<Abstract...	{ "references": [ "phrase-based word embedding,Abstract Syntax Tree(AST)" ], "type": "extractive" }
1910.11471	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What programming language is target language? Context: <<<Title>>> Machine Translation from Natural Language to Code using Long-Short Term Memory <<<Abstract>>> Making computer programming ...	{ "references": [ "Python" ], "type": "extractive" }
1910.11471	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What dataset is used to measure accuracy? Context: <<<Title>>> Machine Translation from Natural Language to Code using Long-Short Term Memory <<<Abstract>>> Making computer programming lang...	{ "references": [ "validation data" ], "type": "extractive" }
1910.09399	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Is text-to-image synthesis trained is suppervized or unsuppervized manner? Context: <<<Title>>> A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis <<<Abstract>...	{ "references": [ "unsupervised ", "Even though natural language and image synthesis were part of several contributions on the supervised side of deep learning, unsupervised learning saw recently a tremendous rise in input from the research community specially on two subproblems: text-based natural language a...
1910.09399	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What challenges remain unresolved? Context: <<<Title>>> A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis <<<Abstract>>> Text-to-image synthesis refers to com...	{ "references": [ "give more independence to the several learning methods (e.g. less human intervention) involved in the studies,increasing the size of the output images" ], "type": "extractive" }
1910.09399	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What is the conclusion of comparison of proposed solution? Context: <<<Title>>> A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis <<<Abstract>>> Text-to-image...	{ "references": [ "HDGAN produced relatively better visual results on the CUB and Oxford datasets while AttnGAN produced far more impressive results than the rest on the more complex COCO dataset,In terms of inception score (IS), which is the metric that was applied to majority models except DC-GAN, the results i...
1910.04601	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What is the baseline? Context: <<<Title>>> RC-QED: Evaluating Natural Language Derivations in Multi-Hop Reading Comprehension <<<Abstract>>> Recent studies revealed that reading comprehensi...	{ "references": [ " path ranking-based KGC (PRKGC)" ], "type": "extractive" }
1910.04601	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What dataset was used in the experiment? Context: <<<Title>>> RC-QED: Evaluating Natural Language Derivations in Multi-Hop Reading Comprehension <<<Abstract>>> Recent studies revealed that ...	{ "references": [ "WikiHop" ], "type": "extractive" }
1910.04601	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Did they use any crowdsourcing platform? Context: <<<Title>>> RC-QED: Evaluating Natural Language Derivations in Multi-Hop Reading Comprehension <<<Abstract>...	{ "references": [ "Yes" ], "type": "boolean" }
1910.04601	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How was the dataset annotated? Context: <<<Title>>> RC-QED: Evaluating Natural Language Derivations in Multi-Hop Reading Comprehension <<<Abstract>>> Recent studies revealed that reading co...	{ "references": [ "True, Likely (i.e. Answerable), or Unsure (i.e. Unanswerable),why they are unsure from two choices (“Not stated in the article” or “Other”),The “summary” text boxes" ], "type": "extractive" }
1912.05066	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How many label options are there in the multi-label task? Context: <<<Title>>> Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds <<<Abstract>>> Sentiment...	{ "references": [ " two labels " ], "type": "extractive" }
1912.05066	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Who are the experts? Context: <<<Title>>> Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds <<<Abstract>>> Sentiment Analysis of microblog feeds has attr...	{ "references": [ "political pundits of the Washington Post", "the experts in the field" ], "type": "extractive" }
1912.05066	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Who is the crowd in these experiments? Context: <<<Title>>> Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds <<<Abstract>>> Sentiment Analysis of microb...	{ "references": [ " peoples' sentiments expressed over social media" ], "type": "extractive" }
1912.05066	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How do you establish the ground truth of who won a debate? Context: <<<Title>>> Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds <<<Abstract>>> Sentimen...	{ "references": [ "experts in Washington Post" ], "type": "extractive" }
1910.03891	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What further analysis is done? Context: <<<Title>>> Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding <<...	{ "references": [ "we use t-SNE tool BIBREF27 to visualize the learned embedding" ], "type": "extractive" }
1910.03891	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What seven state-of-the-art methods are used for comparison? Context: <<<Title>>> Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancin...	{ "references": [ "TransE, TransR and TransH,PTransE, and ALL-PATHS,R-GCN BIBREF24 and KR-EAR BIBREF26" ], "type": "extractive" }
1910.03891	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What three datasets are used to measure performance? Context: <<<Title>>> Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowle...	{ "references": [ "FB24K,DBP24K,Game30K", "Freebase BIBREF0, DBpedia BIBREF1 and a self-construction game knowledge graph" ], "type": "extractive" }
1910.03891	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How does KANE capture both high-order structural and attribute information of KGs in an efficient, explicit and unified manner? Context: <<<Title>>> Learning High-order Structural and Attri...	{ "references": [ "To capture both high-order structural information of KGs, we used an attention-based embedding propagation method." ], "type": "extractive" }
1910.03891	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are recent works on knowedge graph embeddings authors mention? Context: <<<Title>>> Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for E...	{ "references": [ "entity types or concepts BIBREF13,relations paths BIBREF17, textual descriptions BIBREF11, BIBREF12,logical rules BIBREF23,deep neural network models BIBREF24" ], "type": "extractive" }
1909.13375	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How they use sequence tagging to answer multi-span questions? Context: <<<Title>>> Tag-based Multi-Span Extraction in Reading Comprehension <<<Abstract>>> With models reaching human perform...	{ "references": [ "To model an answer which is a collection of spans, the multi-span head uses the $\\mathtt {BIO}$ tagging format BIBREF8: $\\mathtt {B}$ is used to mark the beginning of a span, $\\mathtt {I}$ is used to mark the inside of a span and $\\mathtt {O}$ is used to mark tokens not included in a span" ...
1909.13375	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What is the previous model that attempted to tackle multi-span questions as a part of its design? Context: <<<Title>>> Tag-based Multi-Span Extraction in Reading Comprehension <<<Abstract>>...	{ "references": [ "MTMSN BIBREF4" ], "type": "extractive" }
1910.00912	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Which publicly available NLU dataset is used? Context: <<<Title>>> Hierarchical Multi-Task Natural Language Understanding for Cross-domain Conversational AI: HERMIT NLU <<<Abstract>>> We pr...	{ "references": [ "ROMULUS dataset,NLU-Benchmark dataset" ], "type": "extractive" }
1910.00912	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What metrics other than entity tagging are compared? Context: <<<Title>>> Hierarchical Multi-Task Natural Language Understanding for Cross-domain Conversational AI: HERMIT NLU <<<Abstract>>...	{ "references": [ "We also report the metrics in BIBREF7 for consistency,we report the span F1, Exact Match (EM) accuracy of the entire sequence of labels,metric that combines intent and entities" ], "type": "extractive" }
1908.10449	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Do they provide decision sequences as supervision while training models? Context: <<<Title>>> Interactive Machine Comprehension with Information Seeking Agen...	{ "references": [ "No" ], "type": "boolean" }
1908.10449	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How do they train models in this setup? Context: <<<Title>>> Interactive Machine Comprehension with Information Seeking Agents <<<Abstract>>> Existing machine reading comprehension (MRC) mo...	{ "references": [ "Thus, our task requires models to `feed themselves' rather than spoon-feeding them with information. This casts MRC as a sequential decision-making problem amenable to reinforcement learning (RL)." ], "type": "extractive" }
1908.10449	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What commands does their setup provide to models seeking information? Context: <<<Title>>> Interactive Machine Comprehension with Information Seeking Agents <<<Abstract>>> Existing machine ...	{ "references": [ "previous,next,Ctrl+F $<$query$>$,stop" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What models do they propose? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we target the problem of hate speech detection in mu...	{ "references": [ "Feature Concatenation Model (FCM),Spatial Concatenation Model (SCM),Textual Kernels Model (TKM)" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How large is the dataset? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we target the problem of hate speech detection in multi...	{ "references": [ " $150,000$ tweets" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What is author's opinion on why current multimodal models cannot outperform models analyzing only text? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Ab...	{ "references": [ "Noisy data,Complexity and diversity of multimodal relations,Small set of multimodal examples" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What metrics are used to benchmark the results? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we target the problem of hate spe...	{ "references": [ "F-score,Area Under the ROC Curve (AUC),mean accuracy (ACC),Precision vs Recall plot,ROC curve (which plots the True Positive Rate vs the False Positive Rate)" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How is data collected, manual collection or Twitter api? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we target the problem of...	{ "references": [ "Twitter API" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How many tweats does MMHS150k contains, 150000? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we target the problem of hate spe...	{ "references": [ "$150,000$ tweets" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What unimodal detection models were used? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we target the problem of hate speech de...	{ "references": [ " single layer LSTM with a 150-dimensional hidden state for hate / not hate classification" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What different models for multimodal detection were proposed? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we target the probl...	{ "references": [ "Feature Concatenation Model (FCM),Spatial Concatenation Model (SCM),Textual Kernels Model (TKM)" ], "type": "extractive" }
1910.03814	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What annotations are available in the dataset - tweat used hate speach or not? Context: <<<Title>>> Exploring Hate Speech Detection in Multimodal Publications <<<Abstract>>> In this work we...	{ "references": [ "No attacks to any community, racist,sexist,homophobic,religion based attacks,attacks to other communities" ], "type": "extractive" }
1912.00871	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Does pre-training on general text corpus improve performance? Context: <<<Title>>> Solving Arithmetic Word Problems Automatically Using Transformer and Unamb...	{ "references": [ "No" ], "type": "boolean" }
1912.00871	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What neural configurations are explored? Context: <<<Title>>> Solving Arithmetic Word Problems Automatically Using Transformer and Unambiguous Representations <<<Abstract>>> Constructing ac...	{ "references": [ "tried many configurations of our network models, but report results with only three configurations,Transformer Type 1,Transformer Type 2,Transformer Type 3" ], "type": "extractive" }
1912.00871	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Are the Transformers masked? Context: <<<Title>>> Solving Arithmetic Word Problems Automatically Using Transformer and Unambiguous Representations <<<Abstrac...	{ "references": [ "Yes" ], "type": "boolean" }
1912.00871	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How is this problem evaluated? Context: <<<Title>>> Solving Arithmetic Word Problems Automatically Using Transformer and Unambiguous Representations <<<Abstract>>> Constructing accurate and...	{ "references": [ "BLEU-2,average accuracies over 3 test trials on different randomly sampled test sets" ], "type": "extractive" }
1912.00871	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What datasets do they use? Context: <<<Title>>> Solving Arithmetic Word Problems Automatically Using Transformer and Unambiguous Representations <<<Abstract>>> Constructing accurate and aut...	{ "references": [ "AI2 BIBREF2,CC BIBREF19,IL BIBREF4,MAWPS BIBREF20" ], "type": "extractive" }
1911.11750	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What representations for textual documents do they use? Context: <<<Title>>> A Measure of Similarity in Textual Data Using Spearman's Rank Correlation Coefficient <<<Abstract>>> In the last...	{ "references": [ "finite sequence of terms" ], "type": "extractive" }
1911.11750	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Which dataset(s) do they use? Context: <<<Title>>> A Measure of Similarity in Textual Data Using Spearman's Rank Correlation Coefficient <<<Abstract>>> In the last decade, many diverse adva...	{ "references": [ "14 TDs,BIBREF15" ], "type": "extractive" }
1911.11750	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How do they evaluate knowledge extraction performance? Context: <<<Title>>> A Measure of Similarity in Textual Data Using Spearman's Rank Correlation Coefficient <<<Abstract>>> In the last ...	{ "references": [ "SRCC" ], "type": "extractive" }
1911.03894	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What is CamemBERT trained on? Context: <<<Title>>> CamemBERT: a Tasty French Language Model <<<Abstract>>> Pretrained language models are now ubiquitous in Natural Language Processing. Desp...	{ "references": [ "unshuffled version of the French OSCAR corpus" ], "type": "extractive" }
1911.03894	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Which tasks does CamemBERT not improve on? Context: <<<Title>>> CamemBERT: a Tasty French Language Model <<<Abstract>>> Pretrained language models are now ubiquitous in Natural Language Pro...	{ "references": [ "its performance still lags behind models trained on the original English training set in the TRANSLATE-TEST setting, 81.2 vs. 82.91 for RoBERTa" ], "type": "extractive" }
1911.03894	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How much better was results of CamemBERT than previous results on these tasks? Context: <<<Title>>> CamemBERT: a Tasty French Language Model <<<Abstract>>> Pretrained language models are no...	{ "references": [ "2.36 point increase in the F1 score with respect to the best SEM architecture,on the TRANSLATE-TRAIN setting (81.2 vs. 80.2 for XLM),lags behind models trained on the original English training set in the TRANSLATE-TEST setting, 81.2 vs. 82.91 for RoBERTa,For POS tagging, we observe error reduct...
1911.03894	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Was CamemBERT compared against multilingual BERT on these tasks? Context: <<<Title>>> CamemBERT: a Tasty French Language Model <<<Abstract>>> Pretrained lang...	{ "references": [ "Yes" ], "type": "boolean" }
1911.03894	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What data is used for training CamemBERT? Context: <<<Title>>> CamemBERT: a Tasty French Language Model <<<Abstract>>> Pretrained language models are now ubiquitous in Natural Language Proc...	{ "references": [ "unshuffled version of the French OSCAR corpus" ], "type": "extractive" }
1912.01673	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Is this dataset publicly available? Context: <<<Title>>> COSTRA 1.0: A Dataset of Complex Sentence Transformations <<<Abstract>>> COSTRA 1.0 is a dataset of ...	{ "references": [ "Yes" ], "type": "boolean" }
1912.01673	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Are some baseline models trained on this dataset? Context: <<<Title>>> COSTRA 1.0: A Dataset of Complex Sentence Transformations <<<Abstract>>> COSTRA 1.0 is...	{ "references": [ "Yes" ], "type": "boolean" }
1912.01673	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Do they do any analysis of of how the modifications changed the starting set of sentences? Context: <<<Title>>> COSTRA 1.0: A Dataset of Complex Sentence Tra...	{ "references": [ "Yes" ], "type": "boolean" }
1912.01673	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How do they introduce language variation? Context: <<<Title>>> COSTRA 1.0: A Dataset of Complex Sentence Transformations <<<Abstract>>> COSTRA 1.0 is a dataset of Czech complex sentence tra...	{ "references": [ " we were looking for original and uncommon sentence change suggestions" ], "type": "extractive" }
1912.01673	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Do they use external resources to make modifications to sentences? Context: <<<Title>>> COSTRA 1.0: A Dataset of Complex Sentence Transformations <<<Abstract...	{ "references": [ "No" ], "type": "boolean" }
1909.00088	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Does the model proposed beat the baseline models for all the values of the masking parameter tested? Context: <<<Title>>> Keep Calm and Switch On! Preserving...	{ "references": [ "No" ], "type": "boolean" }
1909.00088	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Has STES been previously used in the literature to evaluate similar tasks? Context: <<<Title>>> Keep Calm and Switch On! Preserving Sentiment and Fluency in ...	{ "references": [ "No" ], "type": "boolean" }
1909.00088	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are the baseline models mentioned in the paper? Context: <<<Title>>> Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text Exchange <<<Abstract>>> In this paper, w...	{ "references": [ "Noun WordNet Semantic Text Exchange Model (NWN-STEM),General WordNet Semantic Text Exchange Model (GWN-STEM),Word2Vec Semantic Text Exchange Model (W2V-STEM)" ], "type": "extractive" }
1911.03385	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Is this style generator compared to some baseline? Context: <<<Title>>> Low-Level Linguistic Controls for Style Transfer and Content Preservation <<<Abstract...	{ "references": [ "Yes" ], "type": "boolean" }
1911.03385	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How they perform manual evaluation, what is criteria? Context: <<<Title>>> Low-Level Linguistic Controls for Style Transfer and Content Preservation <<<Abstract>>> Despite the success of st...	{ "references": [ "accuracy" ], "type": "extractive" }
1911.03385	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What metrics are used for automatic evaluation? Context: <<<Title>>> Low-Level Linguistic Controls for Style Transfer and Content Preservation <<<Abstract>>> Despite the success of style tr...	{ "references": [ "classification accuracy,BLEU scores,model perplexities of the reconstruction" ], "type": "extractive" }
1911.03385	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How they know what are content words? Context: <<<Title>>> Low-Level Linguistic Controls for Style Transfer and Content Preservation <<<Abstract>>> Despite the success of style transfer in ...	{ "references": [ " words found in the control word lists are then removed,The remaining words, which represent the content" ], "type": "extractive" }
1911.03385	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How they model style as a suite of low-level linguistic controls, such as frequency of pronouns, prepositions, and subordinate clause constructions? Context: <<<Title>>> Low-Level Linguisti...	{ "references": [ "style of a sentence is represented as a vector of counts of closed word classes (like personal pronouns) as well as counts of syntactic features like the number of SBAR non-terminals in its constituency parse, since clause structure has been shown to be indicative of style" ], "type": "extr...
2001.07209	Please answer the following question with yes or no based on the given text. You only need to output 'Yes' or 'No' without any additional explanation. Question: Does the paper discuss previous models which have been applied to the same task? Context: <<<Title>>> Text-based inference of moral sentiment change <<<Abstr...	{ "references": [ "Yes" ], "type": "boolean" }
2001.07209	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How does the parameter-free model work? Context: <<<Title>>> Text-based inference of moral sentiment change <<<Abstract>>> We present a text-based framework for investigating moral sentimen...	{ "references": [ "A Centroid model summarizes each set of seed words by its expected vector in embedding space, and classifies concepts into the class of closest expected embedding in Euclidean distance following a softmax rule;,A Naïve Bayes model considers both mean and variance, under the assumption of indepe...
2001.07209	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: Which fine-grained moral dimension examples do they showcase? Context: <<<Title>>> Text-based inference of moral sentiment change <<<Abstract>>> We present a text-based framework for invest...	{ "references": [ "Care / Harm, Fairness / Cheating, Loyalty / Betrayal, Authority / Subversion, and Sanctity / Degradation" ], "type": "extractive" }
2001.10161	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How well did the system do? Context: <<<Title>>> Bringing Stories Alive: Generating Interactive Fiction Worlds <<<Abstract>>> World building forms the foundation of any task that requires n...	{ "references": [ "the neural approach is generally preferred by a greater percentage of participants than the rules or random,human-made game outperforms them all" ], "type": "extractive" }
2001.10161	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: How is the information extracted? Context: <<<Title>>> Bringing Stories Alive: Generating Interactive Fiction Worlds <<<Abstract>>> World building forms the foundation of any task that requ...	{ "references": [ "neural question-answering technique to extract relations from a story text,OpenIE5, a commonly used rule-based information extraction technique" ], "type": "extractive" }
1909.00279	Please extract a concise answer without any additional explanation for the following question based on the given text. Question: What are some guidelines in writing input vernacular so model can generate Context: <<<Title>>> Generating Classical Chinese Poems from Vernacular Chinese <<<Abstract>>> Classical Chinese ...	{ "references": [ " if a vernacular paragraph contains more poetic images used in classical literature, its generated poem usually achieves higher score,poems generated from descriptive paragraphs achieve higher scores than from logical or philosophical paragraphs" ], "type": "extractive" }

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