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Embracing Ambiguity: Shifting the Training Target of NLI Models ...
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Can Question Generation Debias Question Answering Models? A Case Study on Question-Context Lexical Overlap ...
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An Evaluation Dataset for Identifying Communicative Functions of Sentences in English Scholarly Papers
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In: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) ; 12th Conference on Language Resources and Evaluation (LREC 2020) ; https://hal.archives-ouvertes.fr/hal-03272825 ; 12th Conference on Language Resources and Evaluation (LREC 2020), May 2020, Marseille, France (2020)
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Keyphrase Generation for Scientific Document Retrieval
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In: The 58th Annual Meeting of the Association for Computational Linguistics (ACL) ; https://hal.archives-ouvertes.fr/hal-02556086 ; The 58th Annual Meeting of the Association for Computational Linguistics (ACL), Jul 2020, Online, United States. ⟨10.18653/v1/2020.acl-main.105⟩ (2020)
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A Linguistic Analysis of Visually Grounded Dialogues Based on Spatial Expressions ...
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Abstract:
Recent models achieve promising results in visually grounded dialogues. However, existing datasets often contain undesirable biases and lack sophisticated linguistic analyses, which make it difficult to understand how well current models recognize their precise linguistic structures. To address this problem, we make two design choices: first, we focus on OneCommon Corpus \citep{udagawa2019natural,udagawa2020annotated}, a simple yet challenging common grounding dataset which contains minimal bias by design. Second, we analyze their linguistic structures based on \textit{spatial expressions} and provide comprehensive and reliable annotation for 600 dialogues. We show that our annotation captures important linguistic structures including predicate-argument structure, modification and ellipsis. In our experiments, we assess the model's understanding of these structures through reference resolution. We demonstrate that our annotation can reveal both the strengths and weaknesses of baseline models in essential ... : 16 pages, Findings of EMNLP 2020 ...
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Keyword:
Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2010.03127 https://arxiv.org/abs/2010.03127
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Multi-sense Embeddings through a Word Sense Disambiguation Process
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Leveraging Monolingual Data for Crosslingual Compositional Word Representations ...
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Looking for Transliterations in a Trilingual English, French and Japanese Specialised Comparable Corpus
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In: LREC Workshop on Comparable Corpora (LREC'08) ; Language Resources and Evaluation Conference ; https://hal.archives-ouvertes.fr/hal-00417726 ; Language Resources and Evaluation Conference, May 2008, Marrakech, Morocco. pp.4 (2008)
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