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LLM hallucination, where unfaithful text is generated, presents a critical challenge for LLMs' practical applications.
The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2019 · 1904
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Large language models in medicine
Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel Shu Wei Ting. 2023 · 1940
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The Kolmogorov-Smirnov test for goodness of fit
Frank J Massey Jr. 1951 · 1951
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Scheduled sampling for sequence prediction with recurrent neural networks
Samy Bengio, Oriol Vinyals, Navdeep Jaitly, and Noam Shazeer. 2015 · 2015
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spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing
Matthew Honnibal and Ines Montani. 2017 · 2017
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer. 2017 · 2017
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On NMT search errors and model errors: Cat got your tongue?
Felix Stahlberg and Bill Byrne. 2019 · 2019
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Truthfulqa: Measuring how models mimic human falsehoods
Stephanie Lin, Jacob Hilton, and Owain Evans. 2021 · 2021
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Keywordmap: Attention-based visual exploration for keyword analysis
Yamei Tu, Jiayi Xu, and Han-Wei Shen. 2021 · 2021
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The survey: Text generation models in deep learning
Touseef Iqbal and Shaima Qureshi. 2022 · 2022
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Language models (mostly) know what they know
Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield-Dodds, Nova DasSarma, Eli Tran-Johnson, et al. 2022 · 2022
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Locating and editing factual associations in gpt
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022
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The internal state of an LLM knows when it’s lying
Amos Azaria and Tom Mitchell. 2023 · 2023
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Lawyer Used ChatGPT In Court—And Cited Fake Cases. A Judge Is Considering Sanctions
Molly Bohannon. 2023 · 2023
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Hallucination detection: Robustly discerning reliable answers in large language models
Yuyan Chen, Qiang Fu, Yichen Yuan, Zhihao Wen, Ge Fan, Dayiheng Liu, Dongmei Zhang, Zhixu Li, and Yanghua Xiao. 2023 · 2023
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Chainpoll: A high efficacy method for llm hallucination detection
Robert Friel and Atindriyo Sanyal. 2023 · 2023
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Sok: Memorization in general-purpose large language models
Valentin Hartmann, Anshuman Suri, Vincent Bindschaedler, David Evans, Shruti Tople, and Robert West. 2023 · 2023
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Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
Cited alongside, same era.
Large language models struggle to learn long-tail knowledge
Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2023 · 2023
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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 · 2023
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When not to trust language models: Investigating effectiveness of parametric and non-parametric memories
Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Daniel Khashabi, and Hannaneh Hajishirzi. 2023 · 2023
Cited alongside, same era.
Selfcheckgpt: Zero-resource black-box hallucination detection for generative large language models
Jiawei Gu, Xuhui Jiang, Zhichao Shi, Hexiang Tan, Xuehao Zhai, Chengjin Xu, Wei Li, Yinghan Shen, Shengjie Ma, Honghao Liu, et al. 2024 · 2024
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A probabilistic framework for llm hallucination detection via belief tree propagation
Bairu Hou, Yang Zhang, Jacob Andreas, and Shiyu Chang. 2024 · 2024
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Can knowledge editing really correct hallucinations?
Baixiang Huang, Canyu Chen, Xiongxiao Xu, Ali Payani, and Kai Shu. 2024 · 2024
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LLM internal states reveal hallucination risk faced with a query
Ziwei Ji, Delong Chen, Etsuko Ishii, Samuel Cahyawijaya, Yejin Bang, Bryan Wilie, and Pascale Fung. 2024 · 2024
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LLM challenges and solutions
Uday Kamath, Kevin Keenan, Garrett Somers, and Sarah Sorenson. 2024 · 2024
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Potsawee Manakul, Adian Liusie, and Mark JF Gales. 2023 · 2023
Cited alongside, same era.
Knowledge injection to counter large language model (llm) hallucination
Ariana Martino, Michael Iannelli, and Coleen Truong. 2023 · 2023
Cited alongside, same era.
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 · 2023
Cited alongside, same era.
The curious case of hallucinatory (un) answerability: Finding truths in the hidden states of over-confident large language models
Aviv Slobodkin, Omer Goldman, Avi Caciularu, Ido Dagan, and Shauli Ravfogel. 2023 · 2023
Cited alongside, same era.
Kai Sun, Yifan Ethan Xu, Hanwen Zha, Yue Liu, and Xin Luna Dong. 2023 · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
Cited alongside, same era.
Bloomberggpt: A large language model for finance
Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kambadur, David Rosenberg, and Gideon Mann. 2023 · 2023
Cited alongside, same era.
Mars: Meaning-aware response scoring for uncertainty estimation in generative llms
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Baturalp Buyukates, Chenyang Tao, Dimitrios Dimitriadis, and Salman Avestimehr. 2024 · 2024
Cited alongside, same era.
Closest in time.
Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs
Jannik Kossen, Jiatong Han, Muhammed Razzak, Lisa Schut, Shreshth Malik, and Yarin Gal. 2024 · 2024
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Know the unknown: An uncertainty-sensitive method for llm instruction tuning
Jiaqi Li, Yixuan Tang, and Yi Yang. 2024 · 2024
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Detecting hallucinations in large language model generation: A token probability approach
Ernesto Quevedo, Jorge Yero, Rachel Koerner, Pablo Rivas, and Tomas Cerny. 2024 · 2024
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Evaluating consistency and reasoning capabilities of large language models
Yash Saxena, Sarthak Chopra, and Arunendra Mani Tripathi. 2024 · 2024
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Unsupervised real-time hallucination detection based on the internal states of large language models
Weihang Su, Changyue Wang, Qingyao Ai, Yiran Hu, Zhijing Wu, Yujia Zhou, and Yiqun Liu. 2024 · 2024
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MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents
Liyan Tang, Philippe Laban, and Greg Durrett. 2024 · 2024
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Qwen2.5: A party of foundation models
Qwen Team. 2024 · 2024
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Bayesian prompt ensembles: Model uncertainty estimation for black-box large language models
Francesco Tonolini, Nikolaos Aletras, Jordan Massiah, and Gabriella Kazai. 2024 · 2024
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Do not design, learn: A trainable scoring function for uncertainty estimation in generative llms
Duygu Nur Yaldiz, Yavuz Faruk Bakman, Baturalp Buyukates, Chenyang Tao, Anil Ramakrishna, Dimitrios Dimitriadis, Jieyu Zhao, and Salman Avestimehr. 2024 · 2024
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Attributive reasoning for hallucination diagnosis of large language models
Yuyan Chen, Zehao Li, Shuangjie You, Zhengyu Chen, Jingwen Chang, Yi Zhang, Weinan Dai, Qingpei Guo, and Yanghua Xiao. 2025 · 2025
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Enhancing hallucination detection through noise injection
Litian Liu, Reza Pourreza, Sunny Panchal, Apratim Bhattacharyya, Yao Qin, and Roland Memisevic. 2025 · 2025
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