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Leveraging Past References for Robust Language Grounding
Published 2021“…© 2019 Association for Computational Linguistics. Grounding referring expressions to objects in an environment has traditionally been considered a one-off, ahistorical task. …”
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Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers
Published 2022“…© 2019 Association for Computational Linguistics This paper explores the task of leveraging typology in the context of cross-lingual dependency parsing. …”
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Linking artificial and human neural representations of language
Published 2021“…© 2019 Association for Computational Linguistics What information from an act of sentence understanding is robustly represented in the human brain? …”
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Syntactic dependencies correspond to word pairs with high mutual information
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Human-centric dialog training via offline reinforcement learning
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Comparing Models of Associative Meaning: An Empirical Investigation of Reference in Simple Language Games
Published 2021“…© 2018 Association for Computational Linguistics. Simple reference games (Wittgenstein, 1953) are of central theoretical and empirical importance in the study of situated language use. …”
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Representation of Constituents in Neural Language Models: Coordination Phrase as a Case Study
Published 2021“…© 2019 Association for Computational Linguistics Neural language models have achieved state-of-the-art performances on many NLP tasks, and recently have been shown to learn a number of hierarchically-sensitive syntactic dependencies between individual words. …”
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Towards Debiasing Fact Verification Models
Published 2021“…© 2019 Association for Computational Linguistics Fact verification requires validating a claim in the context of evidence. …”
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