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Trained BERT models for phrase alignment with the constrained tree edit distance algorithm ...
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Trained BERT models for phrase alignment with the constrained tree edit distance algorithm ...
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Definition Modelling for Appropriate Specificity ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.194/ Abstract: Definition generation techniques aim to generate a definition of a target word or phrase given a context. In previous studies, researchers have faced various issues such as the out-of-vocabulary problem and over/under-specificity problems. Over-specific definitions present narrow word meanings, whereas under-specific definitions present general and context-insensitive meanings. Herein, we propose a method for definition generation with appropriate specificity. The proposed method addresses the aforementioned problems by leveraging a pre-trained encoder-decoder model, namely Text-to-Text Transfer Transformer, and introducing a re-ranking mechanism to model specificity in definitions. Experimental results on standard evaluation datasets indicate that our method significantly outperforms the previous state-of-the-art method. Moreover, manual evaluation confirms that our method effectively addresses the over/under-specificity problems. ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Processing
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URL: https://underline.io/lecture/37374-definition-modelling-for-appropriate-specificity https://dx.doi.org/10.48448/4nae-d163
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Distinct Label Representations for Few-Shot Text Classification ...
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Language-agnostic Representation from Multilingual Sentence Encoders for Cross-lingual Similarity Estimation ...
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Distilling Word Meaning in Context from Pre-trained Language Models ...
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A Corpus for English-Japanese Multimodal Neural Machine Translation with Comparable Sentences ...
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Lexically Cohesive Neural Machine Translation with Copy Mechanism ...
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