May 14, 2024, 4:50 a.m. | Haixia Han, Jiaqing Liang, Jie Shi, Qianyu He, Yanghua Xiao

cs.CL updates on

arXiv:2401.07301v2 Announce Type: replace
Abstract: Generative Language Models (LMs) such as ChatGPT have exhibited remarkable performance across various downstream tasks. Nevertheless, one of their most prominent drawbacks is generating inaccurate or false information with a confident tone. Previous studies have devised sophisticated pipelines and prompts to induce large LMs to exhibit the capability for self-correction. However, large LMs are explicitly prompted to verify and modify its answers separately rather than completing all steps spontaneously like humans. Moreover, these complex prompts …

abstract arxiv capability chatgpt false generative information language language model language models lms performance pipelines prompts replace small small language model studies tasks type

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