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Dedicated to studies primarily investigating the causes, implications, and solutions for the phenomenon where language models generate plausible but incorrect or nonsensical outputs.
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![]() SciTrust 2.0: A Comprehensive Framework for Evaluating Trustworthiness of Large Language Models in Scientific Applications Emily Herron Junqi Yin Feiyi Wang | |||
![]() MR-Align: Meta-Reasoning Informed Factuality Alignment for Large Reasoning Models Xinming Wang Jian Xu Bin Yu Sheng Lian Hongzhu Yi ...Boran Wang Hongming Yang Han Hu Xu-Yao Zhang Cheng-Lin Liu | |||
![]() CPR: Mitigating Large Language Model Hallucinations with Curative Prompt RefinementIEEE International Conference on Systems, Man and Cybernetics (SMC), 2024 | |||
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