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Large Language Models (LLMs) show promising results in language generation and instruction following but frequently "hallucinate", making their outputs less reliable.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019a · 1908
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Uncertainty estimation in autoregressive structured prediction
Andrey Malinin and Mark Gales. 2020 · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Andrey Malinin, Sergey Chervontsev, Ivan Provilkov, and Mark Gales. 2020 · 2006
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Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits. 2020 · 2009
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei. 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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What uncertainties do we need in bayesian deep learning for computer vision?
Alex Kendall and Yarin Gal. 2017 · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell. 2017 · 2017
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Crowdsourcing multiple choice science questions
Johannes Welbl, Nelson F. Liu, and Matt Gardner. 2017 · 2017
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Analyzing uncertainty in neural machine translation
Myle Ott, Michael Auli, David Grangier, and Marc’Aurelio Ranzato. 2018 · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Coqa: A conversational question answering challenge
Siva Reddy, Danqi Chen, and Christopher D Manning. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019b · 2019
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Unsupervised quality estimation for neural machine translation
Marina Fomicheva, Shuo Sun, Lisa Yankovskaya, Frédéric Blain, Francisco Guzmán, Mark Fishel, Nikolaos Aletras, Vishrav Chaudhary, and Lucia Specia. 2020 · 2020
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Uncertainty-aware machine translation evaluation
Taisiya Glushkova, Chrysoula Zerva, Ricardo Rei, and André FT Martins. 2021 · 2021
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What disease does this patient have? a large-scale open domain question answering dataset from medical exams
Di Jin, Eileen Pan, Nassim Oufattole, Wei-Hung Weng, Hanyi Fang, and Peter Szolovits. 2021 · 2021
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Deup: Direct epistemic uncertainty prediction
Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor Ion Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, and Yoshua Bengio. 2021 · 2021
Science in the age of large language models
Abeba Birhane, Atoosa Kasirzadeh, David Leslie, and Sandra Wachter. 2023 · 2023
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Chatcot: Tool-augmented chain-of-thought reasoning on chat-based large language models
Zhipeng Chen, Kun Zhou, Beichen Zhang, Zheng Gong, Wayne Xin Zhao, and Ji-Rong Wen. 2023 · 2023
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Trueteacher: Learning factual consistency evaluation with large language models
Zorik Gekhman, Jonathan Herzig, Roee Aharoni, Chen Elkind, and Idan Szpektor. 2023 · 2023
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Marzena Karpinska and Mohit Iyyer. 2023 · 2023
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Cited alongside, same era.
Uncertainty estimation in autoregressive structured prediction
Andrey Malinin and Mark John Francis Gales. 2021 · 2021
Cited alongside, same era.
Selection-inference: Exploiting large language models for interpretable logical reasoning
Antonia Creswell, Murray Shanahan, and Irina Higgins. 2022 · 2022
Cited alongside, same era.
Towards collaborative neural-symbolic graph semantic parsing via uncertainty
Zi Lin, Jeremiah Zhe Liu, and Jingbo Shang. 2022b · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022
Cited alongside, same era.
Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering
Ankit Pal, Logesh Kumar Umapathi, and Malaikannan Sankarasubbu. 2022 · 2022
Cited alongside, same era.
Dennis Ulmer, Jes Frellsen, and Christian Hardmeier. 2022 · 2022
Cited alongside, same era.
Uncertainty estimation of transformer predictions for misclassification detection
Artem Vazhentsev, Gleb Kuzmin, Artem Shelmanov, Akim Tsvigun, Evgenii Tsymbalov, Kirill Fedyanin, Maxim Panov, Alexander Panchenko, Gleb Gusev, Mikhail Burtsev, et al. 2022 · 2022
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Lorenz Kuhn, Yarin Gal, and Sebastian Farquhar. 2023 · 2023
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Towards healthy ai: Large language models need therapists too
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi, and Kush R. Varshney. 2023 · 2023
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Large language model guided tree-of-thought
Jieyi Long. 2023 · 2023
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Logic-lm: Empowering large language models with symbolic solvers for faithful logical reasoning
Liangming Pan, Alon Albalak, Xinyi Wang, and William Yang Wang. 2023 · 2023
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Human–ai collaboration enables more empathic conversations in text-based peer-to-peer mental health support
Ashish Sharma, Inna W Lin, Adam S Miner, David C Atkins, and Tim Althoff. 2023 · 2023
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Uncertainty-aware natural language inference with stochastic weight averaging
Aarne Talman, Hande Celikkanat, Sami Virpioja, Markus Heinonen, and Jörg Tiedemann. 2023 · 2023
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Wizardlm: Empowering large language models to follow complex instructions
Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, and Daxin Jiang. 2023 · 2023
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Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric. P Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023
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Gtbench: Uncovering the strategic reasoning limitations of llms via game-theoretic evaluations
Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura, Lichao Sun, Elias Stengel-Eskin, Mohit Bansal, Tianlong Chen, and Kaidi Xu. 2024 · 2024
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Decoding compressed trust: Scrutinizing the trustworthiness of efficient llms under compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang, Zhangheng Li, Chulin Xie, Kelsey Lieberman, James Diffenderfer, Brian Bartoldson, Ajay Jaiswal, Kaidi Xu, et al. 2024 · 2024
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Trustllm: Trustworthiness in large language models
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, et al. 2024 · 2024
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A survey on large language model (llm) security and privacy: The good, the bad, and the ugly
Yifan Yao, Jinhao Duan, Kaidi Xu, Yuanfang Cai, Zhibo Sun, and Yue Zhang. 2024 · 2024
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