• Publications
  • Influence
AllenNLP: A Deep Semantic Natural Language Processing Platform
TLDR
AllenNLP is designed to support researchers who want to build novel language understanding models quickly and easily and provides a flexible data API that handles intelligent batching and padding, and a modular and extensible experiment framework that makes doing good science easy. Expand
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
TLDR
A new reading comprehension benchmark, DROP, which requires Discrete Reasoning Over the content of Paragraphs, and presents a new model that combines reading comprehension methods with simple numerical reasoning to achieve 51% F1. Expand
Neural Semantic Parsing with Type Constraints for Semi-Structured Tables
TLDR
A new semantic parsing model for answering compositional questions on semi-structured Wikipedia tables with a state-of-the-art accuracy and type constraints and entity linking are valuable components to incorporate in neural semantic parsers. Expand
Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning
TLDR
This work presents a new crowdsourced dataset containing more than 24K span-selection questions that require resolving coreference among entities in over 4.7K English paragraphs from Wikipedia, and shows that state-of-the-art reading comprehension models perform significantly worse than humans on this benchmark. Expand
Subgroup Detection in Ideological Discussions
TLDR
This paper analyzes the text exchanged between the participants of a discussion to identify the attitude they carry toward each other and towards the various aspects of the discussion topic and uses clustering techniques to cluster these vectors and determine the subgroup membership of each participant. Expand
Iterative Search for Weakly Supervised Semantic Parsing
TLDR
A novel iterative training algorithm is proposed that alternates between searching for consistent logical forms and maximizing the marginal likelihood of the retrieved ones, thus dealing with the problem of spuriousness. Expand
A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers
TLDR
Qasper is presented, a dataset of 5049 questions over 1585 Natural Language Processing papers that is designed to facilitate document-grounded, information-seeking QA, and finds that existing models that do well on other QA tasks do not perform well on answering these questions. Expand
Evaluating NLP Models via Contrast Sets
TLDR
A new annotation paradigm for NLP is proposed that helps to close systematic gaps in the test data, and it is recommended that after a dataset is constructed, the dataset authors manually perturb the test instances in small but meaningful ways that change the gold label, creating contrast sets. Expand
Tharwa: A Large Scale Dialectal Arabic - Standard Arabic - English Lexicon
TLDR
An electronic three-way lexicon, Tharwa, comprising Dialectal Arabic, Modern Standard Arabic and English correspondents is introduced, which is the first resource of its kind bridging multiple variants of Arabic with English and will have a significant impact on both Theoretical Linguistics as well as Computational Linguistic research. Expand
Ontology-Aware Token Embeddings for Prepositional Phrase Attachment
TLDR
Using context-sensitive embeddings in a model for predicting prepositional phrase (PP) attachments improves the accuracy of the PP attachment model by 5.4% absolute points, which amounts to a 34. Expand
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