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Learning from Task Descriptions
Typically, machine learning systems solve new tasks by training on thous...
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IIRC: A Dataset of Incomplete Information Reading Comprehension Questions
Humans often have to read multiple documents to address their informatio...
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MedICaT: A Dataset of Medical Images, Captions, and Textual References
Understanding the relationship between figures and text is key to scient...
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Improving Compositional Generalization in Semantic Parsing
Generalization of models to out-of-distribution (OOD) data has captured ...
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MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics
Posing reading comprehension as a generation problem provides a great de...
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Easy, Reproducible and Quality-Controlled Data Collection with Crowdaq
High-quality and large-scale data are key to success for AI systems. How...
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Understanding Mention Detector-Linker Interaction for Neural Coreference Resolution
Coreference resolution is an important task for discourse-level natural ...
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Latent Compositional Representations Improve Systematic Generalization in Grounded Question Answering
Answering questions that involve multi-step reasoning requires decomposi...
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Obtaining Faithful Interpretations from Compositional Neural Networks
Neural module networks (NMNs) are a popular approach for modeling compos...
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TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions
A critical part of reading is being able to understand the temporal rela...
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Multi-Step Inference for Reasoning Over Paragraphs
Complex reasoning over text requires understanding and chaining together...
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Evaluating NLP Models via Contrast Sets
Standard test sets for supervised learning evaluate in-distribution gene...
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Break It Down: A Question Understanding Benchmark
Understanding natural language questions entails the ability to break do...
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ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension
Reading comprehension is one of the crucial tasks for furthering researc...
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Neural Module Networks for Reasoning over Text
Answering compositional questions that require multiple steps of reasoni...
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Question Answering is a Format; When is it Useful?
Recent years have seen a dramatic expansion of tasks and datasets posed ...
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AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models
Neural NLP models are increasingly accurate but are imperfect and opaque...
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Do NLP Models Know Numbers? Probing Numeracy in Embeddings
The ability to understand and work with numbers (numeracy) is critical f...
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QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions
We introduce the first open-domain dataset, called QuaRTz, for reasoning...
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Global Reasoning over Database Structures for Text-to-SQL Parsing
State-of-the-art semantic parsers rely on auto-regressive decoding, emit...
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Universal Adversarial Triggers for Attacking and Analyzing NLP
Adversarial examples highlight model vulnerabilities and are useful for ...
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Universal Adversarial Triggers for NLP
Adversarial examples highlight model vulnerabilities and are useful for ...
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Reasoning Over Paragraph Effects in Situations
A key component of successfully reading a passage of text is the ability...
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Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning
Machine comprehension of texts longer than a single sentence often requi...
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Compositional Questions Do Not Necessitate Multi-hop Reasoning
Multi-hop reading comprehension (RC) questions are challenging because t...
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Grammar-based Neural Text-to-SQL Generation
The sequence-to-sequence paradigm employed by neural text-to-SQL models ...
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Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsing
Research on parsing language to SQL has largely ignored the structure of...
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Linguistic Knowledge and Transferability of Contextual Representations
Contextual word representations derived from large-scale neural language...
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DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
Reading comprehension has recently seen rapid progress, with systems mat...
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QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships
Many natural language questions require recognizing and reasoning with q...
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AllenNLP: A Deep Semantic Natural Language Processing Platform
This paper describes AllenNLP, a platform for research on deep learning ...
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Deep contextualized word representations
We introduce a new type of deep contextualized word representation that ...
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Simple and Effective Multi-Paragraph Reading Comprehension
We consider the problem of adapting neural paragraph-level question answ...
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Crowdsourcing Multiple Choice Science Questions
We present a novel method for obtaining high-quality, domain-targeted mu...
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Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge
Traditional semantic parsers map language onto compositional, executable...
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