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Recent advances in large language models have enabled the development of viable generative retrieval systems.
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Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023, Toronto, Canada, July 9–14, 2023 , Anna Rogers, Jordan L. Boyd-Graber, and Naoaki Okazaki (Eds.). Association for Computational Linguistics, 4140–4170
Yixin Liu, Alexander R. Fabbri, Pengfei Liu, Yilun Zhao, Linyong Nan, Ruilin Han, Simeng Han, Shafiq Joty, Chien-Sheng Wu, Caiming Xiong, and Dragomir Radev. 2023a · 2023
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Sequencing Matters: A Generate-Retrieve-Generate Model for Building Conversational Agents
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The Archive Query Log: Mining Millions of Search Result Pages of Hundreds of Search Engines from 25 Years of Web Archives. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2023, Taipei, Taiwan, July 23–27, 2023 , Hsin-Hsi Chen, Wei-Jou (Edward) Duh, Hen-Hsen Huang, Makoto P. Kato, Josiane Mothe, and Barbara Poblete (Eds.). ACM, 2848–2860
Jan Heinrich Reimer, Sebastian Schmidt, Maik Fröbe, Lukas Gienapp, Harrisen Scells, Benno Stein, Matthias Hagen, and Martin Potthast. 2023 · 2023
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Leveraging Large Language Models for Multiple Choice Question Answering. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1–5, 2023 . OpenReview.net, 28 pages
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SWAN: A Generic Framework for Auditing Textual Conversational Systems
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ChatGPT Output Regarding Compulsory Vaccination and COVID-19 Vaccine Conspiracy: A Descriptive Study at the Outset of a Paradigm Shift in Online Search for Information
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Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023 , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, 14918–14937
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Wikipedia: Verifiability, not Truth
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A Passage-Level Reading Behavior Model for Mobile Search. In Proceedings of the ACM Web Conference 2023, WWW 2023, Austin, TX, USA, 30 April 2023 – 4 May 2023 , Ying Ding, Jie Tang, Juan F. Sequeda, Lora Aroyo, Carlos Castillo, and Geert-Jan Houben (Eds.). ACM, 3236–3246
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Generate Rather Than Retrieve: Large Language Models are Strong Context Generators. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1–5, 2023 . OpenReview.net, 27 pages
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Automatic Evaluation of Attribution by Large Language Models. In Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore, December 6–10, 2023 , Houda Bouamor, Juan Pino, and Kalika Bali (Eds.). Association for Computational Linguistics, 4615–4635
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Can ChatGPT-like Generative Models Guarantee Factual Accuracy? On the Mistakes of New Generation Search Engines
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DynamicRetriever: A Pre-trained Model-based IR System Without an Explicit Index
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Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels
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