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GreaseLM: Graph REASoning Enhanced Language Models for Question Answering ...
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Human-like informative conversations: Better acknowledgements using conditional mutual information ...
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ContractNLI: A Dataset for Document-level Natural Language Inference for Contracts ...
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Biomedical and clinical English model packages for the Stanza Python NLP library
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In: J Am Med Inform Assoc (2021)
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Stanza: A Python Natural Language Processing Toolkit for Many Human Languages ...
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Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection ...
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Syn-QG: Syntactic and Shallow Semantic Rules for Question Generation ...
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Finding Universal Grammatical Relations in Multilingual BERT ...
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CoQA: A Conversational Question Answering Challenge
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In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 249-266 (2019) (2019)
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Arc-swift: A Novel Transition System for Dependency Parsing ...
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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
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Improving Coreference Resolution by Learning Entity-Level Distributed Representations ...
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Abstract:
A long-standing challenge in coreference resolution has been the incorporation of entity-level information - features defined over clusters of mentions instead of mention pairs. We present a neural network based coreference system that produces high-dimensional vector representations for pairs of coreference clusters. Using these representations, our system learns when combining clusters is desirable. We train the system with a learning-to-search algorithm that teaches it which local decisions (cluster merges) will lead to a high-scoring final coreference partition. The system substantially outperforms the current state-of-the-art on the English and Chinese portions of the CoNLL 2012 Shared Task dataset despite using few hand-engineered features. ... : Accepted for publication at the Association for Computational Linguistics (ACL), 2016 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1606.01323 https://arxiv.org/abs/1606.01323
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A large annotated corpus for learning natural language inference ...
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Text to 3D Scene Generation with Rich Lexical Grounding ...
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Learning Distributed Word Representations for Natural Logic Reasoning ...
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Discovery of Deep Structure from Unlabeled Data
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In: DTIC (2014)
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Induced lexico-syntactic patterns improve information extraction from online medical forums
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