Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework. (arXiv:2305.03268v1 [cs.CL])

As large language models (LLMs) have become the norm in NLP, demonstrating
good performance in generation and reasoning tasks, one of its most fatal
disadvantages is the lack of factual correctness. Generating unfactual texts
not only leads to lower performances but also degrades the trust and validity
of their applications. Chain-of-Thought (CoT) prompting improves trust and
model performance on complex reasoning tasks by generating interpretable
reasoning chains, but still suffers from factuality concerns in
knowledge-intensive tasks. In this paper, we …

applications arxiv become disadvantages framework good knowledge language language models large language models leads llms nlp performance prompting reasoning thought trust verify