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1
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang ...
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2
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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3
Bird's Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
Hou, Yifan; Sachan, Mrinmaya. - : arXiv, 2021
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4
Scaling Within Document Coreference to Long Texts ...
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5
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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6
Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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7
Differentiable Subset Pruning of Transformer Heads ...
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8
How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact ...
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9
How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact ...
Jin, Zhijing; Chauhan, Geeticka; Tse, Brian. - : ETH Zurich, 2021
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10
“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding ...
Abstract: When reading a literary piece, readers often make inferences about various characters’ roles, personalities, relationships, intents, actions, etc. While humans can readily draw upon their past experiences to build such a character-centric view of the narrative, understanding characters in narratives can be a challenging task for machines. To encourage research in this field of character-centric narrative understanding, we present LiSCU – a new dataset of literary pieces and their summaries paired with descriptions of characters that appear in them. We also introduce two new tasks on LiSCU: Character Identification and Character Description Generation. Our experiments with several pre-trained language models adapted for these tasks demonstrate that there is a need for better models of narrative comprehension. ... : Findings of the Association for Computational Linguistics: EMNLP 2021 ...
URL: https://dx.doi.org/10.3929/ethz-b-000527301
http://hdl.handle.net/20.500.11850/527301
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11
Scaling Within Document Coreference to Long Texts ...
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12
Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations ...
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13
Differentiable subset pruning of transformer heads ...
Li, Jiaoda; Cotterell, Ryan; Sachan, Mrinmaya. - : ETH Zurich, 2021
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14
Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations ...
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15
Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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16
How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact
In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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17
Differentiable subset pruning of transformer heads
In: Transactions of the Association for Computational Linguistics, 9 (2021)
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18
Scaling Within Document Coreference to Long Texts
In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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19
“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding
In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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20
Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations
In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021)
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