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Welcome to the Modern World of Pronouns: Identity-Inclusive Natural Language Processing beyond Gender ...
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MultiCite: Modeling realistic citations requires moving beyond the single-sentence single-label setting ...
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Abstract:
Citation context analysis (CCA) is an important task in natural language processing that studies how and why scholars discuss each others' work. Despite decades of study, traditional frameworks for CCA have largely relied on overly-simplistic assumptions of how authors cite, which ignore several important phenomena. For instance, scholarly papers often contain rich discussions of cited work that span multiple sentences and express multiple intents concurrently. Yet, CCA is typically approached as a single-sentence, single-label classification task, and thus existing datasets fail to capture this interesting discourse. In our work, we address this research gap by proposing a novel framework for CCA as a document-level context extraction and labeling task. We release MultiCite, a new dataset of 12,653 citation contexts from over 1,200 computational linguistics papers. Not only is it the largest collection of expert-annotated citation contexts to-date, MultiCite contains multi-sentence, multi-label citation ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2107.00414 https://dx.doi.org/10.48550/arxiv.2107.00414
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RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
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AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings ...
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Rhetoric, Logic, and Dialectic: Advancing Theory-based Argument Quality Assessment in Natural Language Processing ...
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Rhetoric, Logic, and Dialectic: Advancing Theory-based Argument Quality Assessment in Natural Language Processing ...
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Creating a Domain-diverse Corpus for Theory-based Argument Quality Assessment ...
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From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ...
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From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers ...
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity
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Lauscher, Anne; Vulic, Ivan; Ponti, Edoardo. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.118, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020
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From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers
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Specializing unsupervised pretraining models for word-level semantic similarity
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AraWEAT: Multidimensional analysis of biases in Arabic word embeddings
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Common sense or world knowledge? Investigating adapter-based knowledge injection into pretrained transformers
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From zero to hero: On the limitations of zero-shot language transfer with multilingual transformers
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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