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Target-aware Abstractive Related Work Generation with Contrastive Learning.

, , , , , , and . SIGIR, page 373-383. ACM, (2022)

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Meaningful Answer Generation of E-Commerce Question-Answering., , , , and . CoRR, (2020)Follow the Timeline! Generating an Abstractive and Extractive Timeline Summary in Chronological Order., , , , , , , and . ACM Trans. Inf. Syst., 41 (1): 9:1-9:30 (January 2023)Modeling non-uniform uncertainty in Reaction Prediction via Boosting and Dropout., , , , , , , , and . CoRR, (2023)The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement., , , , , and . CoRR, (2020)Learning to Respond with Stickers: A Framework of Unifying Multi-Modality in Multi-Turn Dialog., , , , , and . WWW, page 1138-1148. ACM / IW3C2, (2020)How does Truth Evolve into Fake News? An Empirical Study of Fake News Evolution., , , , and . WWW (Companion Volume), page 407-411. ACM / IW3C2, (2021)Abstractive Text Summarization by Incorporating Reader Comments., , , , , , and . AAAI, page 6399-6406. AAAI Press, (2019)Combining Curriculum Learning and Knowledge Distillation for Dialogue Generation., , , , and . EMNLP (Findings), page 1284-1295. Association for Computational Linguistics, (2021)Towards Improving Faithfulness in Abstractive Summarization., , , and . NeurIPS, (2022)Summarizing Procedural Text: Data and Approach., , , , and . EMNLP (Findings), page 2216-2225. Association for Computational Linguistics, (2022)