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20242026
most citedLLMAuditor: A Framework for Auditing Large Language Models Using Human-in-the-Loop

3 citations · 4 across the 7 of their papers we have counts for

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cs.CL2024

Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only

Jihan Yao, Wenxuan Ding, Shangbin Feng +2

In the absence of abundant reliable annotations for challenging tasks and contexts, how can we expand the frontier of LLM capabilities with potentially wrong answers? We focus on t…

cs.CL2024★ 1 cited

Know Your Limits: A Survey of Abstention in Large Language Models

Bingbing Wen, Jihan Yao, Shangbin Feng +4

Abstention, the refusal of large language models (LLMs) to provide an answer, is increasingly recognized for its potential to mitigate hallucinations and enhance safety in LLM syst…