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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 CONFIT: Toward Faithful Dialogue Summarization with Linguistically-Informed Contrastive Fine-tuning ... Tang, Xiangru; Nair, Arjun; Wang, Borui; Wang, Bingyao; Desai, Jai; Wade, Aaron; Li, Haoran; Celikyilmaz, Asli; Mehdad, Yashar; Radev, Dragomir. - : arXiv, 2021 Abstract: Factual inconsistencies in generated summaries severely limit the practical applications of abstractive dialogue summarization. Although significant progress has been achieved by using pre-trained models, substantial amounts of hallucinated content are found during the human evaluation. Pre-trained models are most commonly fine-tuned with cross-entropy loss for text summarization, which may not be an optimal strategy. In this work, we provide a typology of factual errors with annotation data to highlight the types of errors and move away from a binary understanding of factuality. We further propose a training strategy that improves the factual consistency and overall quality of summaries via a novel contrastive fine-tuning, called ConFiT. Based on our linguistically-informed typology of errors, we design different modular objectives that each target a specific type. Specifically, we utilize hard negative samples with errors to reduce the generation of factual inconsistency. In order to capture the key ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2112.08713 https://arxiv.org/abs/2112.08713 BASE Hide details 2 AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization ... Fabbri, Alexander R.; Wu, Xiaojian; Iyer, Srini. - : arXiv, 2021 BASE Show details 3 EASE: Extractive-Abstractive Summarization End-to-End using the Information Bottleneck Principle ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Srinivasan; Einolghozati, Arash. - : Underline Science Inc., 2021 BASE Show details 4 ConvoSumm: Conversation Summarization Benchmark and Improved Abstractive Summarization with Argument Mining ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Fabbri, Alexander; Li, Haoran. - : Underline Science Inc., 2021 BASE Show details 5 Syntax-augmented Multilingual BERT for Cross-lingual Transfer ... Ahmad, Wasi Uddin; Li, Haoran; Chang, Kai-Wei. - : arXiv, 2021 BASE Show details 6 Syntax-augmented Multilingual BERT for Cross-lingual Transfer ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Ahmad, Wasi Uddin; Chang, Kai-Wei. - : Underline Science Inc., 2021 BASE Show details 7 MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark ... Li, Haoran; Arora, Abhinav; Chen, Shuohui. - : arXiv, 2020 BASE Show details 8 Emerging Cross-lingual Structure in Pretrained Language Models ... Wu, Shijie; Conneau, Alexis; Li, Haoran. - : arXiv, 2019 BASE Show details

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