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Outline Generation: Understanding the Inherent Content Structure of Documents.

, , , , and . SIGIR, page 745-754. ACM, (2019)

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A Deep Look into neural ranking models for information retrieval., , , , , , , , and . Inf. Process. Manag., 57 (6): 102067 (2020)A Review on Question Generation from Natural Language Text., , , , and . ACM Trans. Inf. Syst., 40 (1): 14:1-14:43 (2022)Semantic Models for the First-Stage Retrieval: A Comprehensive Review., , , , , and . ACM Trans. Inf. Syst., 40 (4): 66:1-66:42 (2022)Dual-factor Generation Model for Conversation., , , , and . ACM Trans. Inf. Syst., 38 (3): 31:1-31:31 (2020)CorpusBrain: Pre-train a Generative Retrieval Model for Knowledge-Intensive Language Tasks., , , , , and . CIKM, page 191-200. ACM, (2022)An Adaptive Framework for Conversational Question Answering., , , , , and . AAAI, page 10041-10042. AAAI Press, (2019)Structure Learning for Headline Generation., , , , and . AAAI, page 9555-9562. AAAI Press, (2020)Learning to Truncate Ranked Lists for Information Retrieval., , , , , and . AAAI, page 4453-4461. AAAI Press, (2021)Prompt Tuning with Contradictory Intentions for Sarcasm Recognition., , , , and . EACL, page 328-339. Association for Computational Linguistics, (2023)CAME: Competitively Learning a Mixture-of-Experts Model for First-stage Retrieval., , , , , , and . CoRR, (2023)