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Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer in Prompt Tuning.

, , , , , , , , and . EACL (1), page 2408-2421. Association for Computational Linguistics, (2024)

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A Tableau Method for Graded Intersections of Modalities: A Case for Concept Languages.. J. Log. Lang. Inf., 11 (1): 67-77 (2002)Temporal Effects on Pre-trained Models for Language Processing Tasks., and . Trans. Assoc. Comput. Linguistics, (2022)Summarization from Leaderboards to Practice: Choosing A Representation Backbone and Ensuring Robustness., , , , , , and . CoRR, (2023)Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer., , , , , , , , and . CoRR, (2023)Combining Lexical and Syntactic Features for Detecting Content-Dense Texts in News., and . J. Artif. Intell. Res., (2017)Class-level spectral features for emotion recognition., , and . Speech Commun., 52 (7-8): 613-625 (2010)Predicting Summary Quality using Limited Human Input., and . TAC, NIST, (2009)User Modelling as an Application of Actors., and . ICCS, volume 1640 of Lecture Notes in Computer Science, page 83-89. Springer, (1999)Automatically Evaluating Content Selection in Summarization without Human Models., and . EMNLP, page 306-314. ACL, (2009)Evaluating Multiple System Summary Lengths: A Case Study., , , , , , and . EMNLP, page 774-778. Association for Computational Linguistics, (2018)