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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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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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Abstract:
Though preceding work in computational argument quality (AQ) mostly focuses on assessing overall AQ, researchers agree that writers would benefit from feedback targeting individual dimensions of argumentation theory. However, a large-scale theory-based corpus and corresponding computational models are missing. We fill this gap by conducting an extensive analysis covering three diverse domains of online argumentative writing and presenting GAQCorpus: the first large-scale English multi-domain (community Q&A forums, debate forums, review forums) corpus annotated with theory-based AQ scores. We then propose the first computational approaches to theory-based assessment, which can serve as strong baselines for future work. We demonstrate the feasibility of large-scale AQ annotation, show that exploiting relations between dimensions yields performance improvements, and explore the synergies between theory-based prediction and practical AQ assessment. ... : accepted for COLING 20 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2006.00843 https://dx.doi.org/10.48550/arxiv.2006.00843
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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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