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The prevalent use of large language models (LLMs) in various domains has drawn attention to the issue of "hallucination," which refers to instances where LLMs generate factually inaccurate or ungrounded information.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 1908
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An introduction to the bootstrap
Bradley Efron and Robert J Tibshirani · 1994
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Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and Mike Lewis · 2004
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Towards faithful neural table-to-text generation with content-matching constraints
Zhenyi Wang, Xiaoyang Wang, Bang An, Dong Yu, and Changyou Chen · 2005
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Guided open vocabulary image captioning with constrained beam search
Peter Anderson, Basura Fernando, Mark Johnson, and Stephen Gould · 2017
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Object hallucination in image captioning
Anna Rohrbach, Lisa Anne Hendricks, Kaylee Burns, Trevor Darrell, and Kate Saenko · 2018
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi · 2019
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On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald · 2020
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On exposure bias, hallucination and domain shift in neural machine translation
Chaojun Wang and Rico Sennrich · 2020
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Detecting hallucinated content in conditional neural sequence generation
Chunting Zhou, Graham Neubig, Jiatao Gu, Mona Diab, Paco Guzman, Luke Zettlemoyer, and Marjan Ghazvininejad · 2020
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Hallucinated but factual! inspecting the factuality of hallucinations in abstractive summarization
Meng Cao, Yue Dong, and Jackie Chi Kit Cheung · 2021
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Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans · 2021
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Retrieval augmentation reduces hallucination in conversation
Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston · 2021
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Sketch and refine: Towards faithful and informative table-to-text generation
Peng Wang, Junyang Lin, An Yang, Chang Zhou, Yichang Zhang, Jingren Zhou, and Hongxia Yang · 2021
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Let there be a clock on the beach: Reducing object hallucination in image captioning
Ali Furkan Biten, Lluís Gómez, and Dimosthenis Karatzas · 2022
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Halueval: A large-scale hallucination evaluation benchmark for large language models
Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen · 2023
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Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models
Potsawee Manakul, Adian Liusie, and Mark JF Gales · 2023
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Factscore: Fine-grained atomic evaluation of factual precision in long form text generation
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, and Hannaneh Hajishirzi · 2023
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Generating benchmarks for factuality evaluation of language models
Dor Muhlgay, Ori Ram, Inbal Magar, Yoav Levine, Nir Ratner, Yonatan Belinkov, Omri Abend, Kevin Leyton-Brown, Amnon Shashua, and Yoav Shoham · 2023
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Self-contradictory hallucinations of large language models: Evaluation, detection and mitigation
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Factuality enhanced language models for open-ended text generation
Nayeon Lee, Wei Ping, Peng Xu, Mostofa Patwary, Pascale N Fung, Mohammad Shoeybi, and Bryan Catanzaro · 2022
Cited alongside, same era.
A token-level reference-free hallucination detection benchmark for free-form text generation
Tianyu Liu, Yizhe Zhang, Chris Brockett, Yi Mao, Zhifang Sui, Weizhu Chen, and William B Dolan · 2022
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Falcon-40b: an open large language model with state-of-the-art performance, 2023
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Merouane Debbah, Etienne Goffinet, Daniel Heslow, Julien Launay, Quentin Malartic, et al · 2023
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Critic: Large language models can self-correct with tool-interactive critiquing
Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen, Yujiu Yang, Nan Duan, and Weizhu Chen · 2023
Cited alongside, same era.
Zero-shot faithful factual error correction
Kung-Hsiang Huang, Hou Pong Chan, and Heng Ji · 2023
Cited alongside, same era.
Mitigating language model hallucination with interactive question-knowledge alignment
Shuo Zhang, Liangming Pan, Junzhou Zhao, and William Yang Wang
Cited in the paper.
Interpretable unified language checking
Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, Wei Fang, Luc Gaitskell, Thomas Hartvigsen, Xixin Wu, Danny Fox, Helen Meng, and James Glass
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Niels Mündler, Jingxuan He, Slobodan Jenko, and Martin Vechev · 2023
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Alpaca: A strong, replicable instruction-following model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto · 2023
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Jian Xie, Kai Zhang, Jiangjie Chen, Renze Lou, and Yu Su · 2023
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Automatic evaluation of attribution by large language models
Xiang Yue, Boshi Wang, Kai Zhang, Ziru Chen, Yu Su, and Huan Sun · 2023
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Judging llm-as-a-judge with mt-bench and chatbot arena
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