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Uncertainty quantification is essential for assessing the reliability and trustworthiness of modern AI systems.
Teaching models to express their uncertainty in words
Stephanie Lin, Jacob Hilton, and Owain Evans. 2022 · 2022
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LM-polygraph: Uncertainty estimation for language models
Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, Artem Vazhentsev, Sergey Petrakov, Kirill Fedyanin, Daniil Vasilev, Elizaveta Goncharova, Alexander Panchenko, Maxim Panov, Timothy Baldwin, and Artem Shelmanov. 2023 · 2023
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Lorenz Kuhn, Yarin Gal, and Sebastian Farquhar. 2023 · 2023
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2023 · 2023
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Just ask for calibration: Strategies for eliciting calibrated confidence scores from language models fine-tuned with human feedback
Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, and Christopher Manning. 2023 · 2023
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Instruction-following evaluation for large language models
Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, Siddhartha Brahma, Sujoy Basu, Yi Luan, Denny Zhou, and Le Hou. 2023 · 2023
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Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna, Baptiste Bout, Devendra Chaplot, Jessica Chudnovsky, Diogo Costa, Baudouin De Monicault, Saurabh Garg, Theophile Gervet, Soham Ghosh, Amélie Héliou, Paul Jacob, Albert Q. Jiang, Kartik Khandelwal, Timothée Lacroix, Guillaume Lample, Diego Las Casas, Thibaut Lavril, and 23 others. 2024 · 2024
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Voicebench: Benchmarking llm-based voice assistants
Yiming Chen, Xianghu Yue, Chen Zhang, Xiaoxue Gao, Robby T. Tan, and Haizhou Li. 2024 · 2024
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Fact-checking the output of large language models via token-level uncertainty quantification
Ekaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, Sergey Petrakov, Haonan Li, Hamdy Mubarak, Evgenii Tsymbalov, Gleb Kuzmin, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, and Maxim Panov. 2024 · 2024
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Isobench: Benchmarking multimodal foundation models on isomorphic representations
Deqing Fu, Ruohao Guo, Ghazal Khalighinejad, Ollie Liu, Bhuwan Dhingra, Dani Yogatama, Robin Jia, and Willie Neiswanger. 2024 · 2024
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Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Alex Vaughan, Amy Yang, Angela Fan, Anirudh Goyal, Anthony Hartshorn, Aobo Yang, Archi Mitra, Archie Sravankumar, Artem Korenev, Arthur Hinsvark, and 542 others. 2024 · 2024
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Overconfidence is key: Verbalized uncertainty evaluation in large language and vision-language models
Tobias Groot and Matias Valdenegro Toro. 2024 · 2024
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Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, and Jianfeng Gao. 2024 · 2024
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Kernel language entropy: Fine-grained uncertainty quantification for llms from semantic similarities
Alexander Nikitin, Jannik Kossen, Yarin Gal, and Pekka Marttinen. 2024 · 2024
Cited alongside, same era.
Vibe-eval: A hard evaluation suite for measuring progress of multimodal language models
Piotr Padlewski, Max Bain, Matthew Henderson, Zhongkai Zhu, Nishant Relan, Hai Pham, Donovan Ong, Kaloyan Aleksiev, Aitor Ormazabal, Samuel Phua, Ethan Yeo, Eugenie Lamprecht, Qi Liu, Yuqi Wang, Eric Chen, Deyu Fu, Lei Li, Che Zheng, Cyprien de Masson d’Autume, and 3 others. 2024 · 2024
Cited alongside, same era.
Benchmarking uncertainty quantification methods for large language models with lm-polygraph
Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev, Lyudmila Rvanova, Daniil Vasilev, Akim Tsvigun, Sergey Petrakov, Rui Xing, Abdelrahman Sadallah, Kirill Grishchenkov, Alexander Panchenko, Timothy Baldwin, Preslav Nakov, Maxim Panov, and Artem Shelmanov. 2024 · 2024
Cited alongside, same era.
Measuring multimodal mathematical reasoning with math-vision dataset
Ke Wang, Junting Pan, Weikang Shi, Zimu Lu, Houxing Ren, Aojun Zhou, Mingjie Zhan, and Hongsheng Li. 2024 · 2024
Cited alongside, same era.
Uncertainty distillation: Teaching language models to express semantic confidence
Sophia Hager, David Mueller, Kevin Duh, and Nicholas Andrews. 2025 · 2025
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Video-mmmu: Evaluating knowledge acquisition from multi-discipline professional videos
Kairui Hu, Penghao Wu, Fanyi Pu, Wang Xiao, Yuanhan Zhang, Xiang Yue, Bo Li, and Ziwei Liu. 2025 · 2025
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Kimi Team, Angang Du, Bohong Yin, Bowei Xing, Bowen Qu, Bowen Wang, Cheng Chen, Chenlin Zhang, Chenzhuang Du, Chu Wei, Congcong Wang, Dehao Zhang, Dikang Du, Dongliang Wang, Enming Yuan, Enzhe Lu, Fang Li, Flood Sung, Guangda Wei, and 73 others. 2025 · 2025
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Cross the gap: Exposing the intra-modal misalignment in clip via modality inversion
Marco Mistretta, Alberto Baldrati, Lorenzo Agnolucci, Marco Bertini, and Andrew D. Bagdanov. 2025 · 2025
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Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms
Miao Xiong, Zhiyuan Hu, Xinyang Lu, Yifei Li, Jie Fu, Junxian He, and Bryan Hooi. 2024 · 2024
Cited alongside, same era.
SaySelf: Teaching LLMs to express confidence with self-reflective rationales
Tianyang Xu, Shujin Wu, Shizhe Diao, Xiaoze Liu, Xingyao Wang, Yangyi Chen, and Jing Gao. 2024 · 2024
Cited alongside, same era.
On verbalized confidence scores for llms
Daniel Yang, Yao-Hung Hubert Tsai, and Makoto Yamada. 2024 · 2024
Cited alongside, same era.
Mmmu-pro: A more robust multi-discipline multimodal understanding benchmark
Xiang Yue, Tianyu Zheng, Yuansheng Ni, Yubo Wang, Kai Zhang, Shengbang Tong, Yuxuan Sun, Botao Yu, Ge Zhang, Huan Sun, Yu Su, Wenhu Chen, and Graham Neubig. 2024 · 2024
Cited alongside, same era.
Shuai Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Sibo Song, Kai Dang, Peng Wang, Shijie Wang, Jun Tang, Humen Zhong, Yuanzhi Zhu, Mingkun Yang, Zhaohai Li, Jianqiang Wan, Pengfei Wang, Wei Ding, Zheren Fu, Yiheng Xu, and 8 others. 2025 · 2025
Cited alongside, same era.
Know what you do not know: Verbalized uncertainty estimation robustness on corrupted images in vision-language models
Mirko Borszukovszki, Ivo Pascal De Jong, and Matias Valdenegro-Toro. 2025 · 2025
Cited alongside, same era.
Unveiling uncertainty: A deep dive into calibration and performance of multimodal large language models
Zijun Chen, Wenbo Hu, Guande He, Zhijie Deng, ZHeng ZHang, and Richang Hong. 2025 · 2025
Cited alongside, same era.
Skywork r1v2: Multimodal hybrid reinforcement learning for reasoning
Chris, Yichen Wei, Yi Peng, Xiaokun Wang, Weijie Qiu, Wei Shen, Tianyidan Xie, Jiangbo Pei, Jianhao Zhang, Yunzhuo Hao, Xuchen Song, Yang Liu, and Yahui Zhou. 2025 · 2025
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OpenAI, :, Ahmed El-Kishky, Alexander Wei, Andre Saraiva, Borys Minaiev, Daniel Selsam, David Dohan, Francis Song, Hunter Lightman, Ignasi Clavera, Jakub Pachocki, Jerry Tworek, Lorenz Kuhn, Lukasz Kaiser, Mark Chen, Max Schwarzer, Mostafa Rohaninejad, Nat McAleese, and 7 others. 2025 · 2025
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Introducing openai o3 and o4-mini
OpenAI. 2025 · 2025
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Skywork r1v: Pioneering multimodal reasoning with chain-of-thought
Yi Peng, Chris, Xiaokun Wang, Yichen Wei, Jiangbo Pei, Weijie Qiu, Ai Jian, Yunzhuo Hao, Jiachun Pan, Tianyidan Xie, Li Ge, Rongxian Zhuang, Xuchen Song, Yang Liu, and Yahui Zhou. 2025 · 2025
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Large vision-language model alignment and misalignment: A survey through the lens of explainability
Dong Shu, Haiyan Zhao, Jingyu Hu, Weiru Liu, Ali Payani, Lu Cheng, and Mengnan Du. 2025 · 2025
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Yanling Wang, Yihan Zhao, Xiaodong Chen, Shasha Guo, Lixin Liu, Haoyang Li, Yong Xiao, Jing Zhang, Qi Li, and Ke Xu. 2025 · 2025
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Do reasoning models show better verbalized calibration?
Qingcheng Zeng, Weihao Xuan, Leyang Cui, and Rob Voigt. 2025 · 2025
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Object-level verbalized confidence calibration in vision-language models via semantic perturbation
Yunpu Zhao, Rui Zhang, Junbin Xiao, Ruibo Hou, Jiaming Guo, Zihao Zhang, Yifan Hao, and Yunji Chen. 2025 · 2025
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Internvl3: Exploring advanced training and test-time recipes for open-source multimodal models
Jinguo Zhu, Weiyun Wang, Zhe Chen, Zhaoyang Liu, Shenglong Ye, Lixin Gu, Hao Tian, Yuchen Duan, Weijie Su, Jie Shao, Zhangwei Gao, Erfei Cui, Xuehui Wang, Yue Cao, Yangzhou Liu, Xingguang Wei, Hongjie Zhang, Haomin Wang, Weiye Xu, and 32 others. 2025 · 2025
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