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Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang ...
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Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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Bird's Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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Bird’s Eye: Probing for Linguistic Graph Structures with a Simple Information-Theoretic Approach ...
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How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact ...
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How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact ...
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Abstract:
Recent years have seen many breakthroughs in natural language processing (NLP), transitioning it from a mostly theoretical field to one with many real-world applications. Noting the rising number of applications of other machine learning and AI techniques with pervasive societal impact, we anticipate the rising importance of developing NLP technologies for social good. Inspired by theories in moral philosophy and global priorities research, we aim to promote a guideline for social good in the context of NLP. We lay the foundations via the moral philosophy definition of social good, propose a framework to evaluate the direct and indirect real-world impact of NLP tasks, and adopt the methodology of global priorities research to identify priority causes for NLP research. Finally, we use our theoretical framework to provide some practical guidelines for future NLP research for social good. ... : Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 ...
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URL: https://dx.doi.org/10.3929/ethz-b-000527311 http://hdl.handle.net/20.500.11850/527311
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“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding ...
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Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations ...
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Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations ...
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Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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How Good Is NLP?A Sober Look at NLP Tasks through the Lens of Social Impact
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In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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Differentiable subset pruning of transformer heads
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In: Transactions of the Association for Computational Linguistics, 9 (2021)
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Scaling Within Document Coreference to Long Texts
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In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 (2021)
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“Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding
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In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations
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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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