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TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing ...
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SpanNER: Named Entity Re-/Recognition as Span Prediction ...
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Align Voting Behavior with Public Statements for Legislator Representation Learning ...
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fastHan: A BERT-based Multi-Task Toolkit for Chinese NLP ...
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{K-Adapter}: {I}nfusing {K}nowledge into {P}re-{T}rained {M}odels with {A}dapters ...
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Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble ...
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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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Classifying Dyads for Militarized Conflict Analysis
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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Efficient Sampling of Dependency Structure
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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Searching for More Efficient Dynamic Programs
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In: Findings of the Association for Computational Linguistics: EMNLP 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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A Bayesian Framework for Information-Theoretic Probing
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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Improving Dialogue State Tracking with Turn-based Loss Function and Sequential Data Augmentation
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Come hither or go away? Recognising pre-electoral coalition signals in the news
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K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters ...
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A Graph-based Model for Joint Chinese Word Segmentation and Dependency Parsing
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In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 78-92 (2020) (2020)
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GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge ...
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Abstract:
Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a particular context. Traditional supervised methods rarely take into consideration the lexical resources like WordNet, which are widely utilized in knowledge-based methods. Recent studies have shown the effectiveness of incorporating gloss (sense definition) into neural networks for WSD. However, compared with traditional word expert supervised methods, they have not achieved much improvement. In this paper, we focus on how to better leverage gloss knowledge in a supervised neural WSD system. We construct context-gloss pairs and propose three BERT-based models for WSD. We fine-tune the pre-trained BERT model on SemCor3.0 training corpus and the experimental results on several English all-words WSD benchmark datasets show that our approach outperforms the state-of-the-art systems. ... : EMNLP-IJCNLP 2019 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1908.07245 https://dx.doi.org/10.48550/arxiv.1908.07245
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Distantly Supervised Named Entity Recognition using Positive-Unlabeled Learning ...
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