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cs.CL2024★ 2 cited
Large Language Models as Code Executors: An Exploratory Study
Chenyang Lyu, Lecheng Yan, Rui Xing +4
The capabilities of Large Language Models (LLMs) have significantly evolved, extending from natural language processing to complex tasks like code understanding and generation. We…
cs.CL2024★ 2 cited
Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models
Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing +7
Uncertainty quantification (UQ) has emerged as a promising approach for detecting hallucinations and low-quality output of Large Language Models (LLMs). However, obtaining proper u…