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cs.CL2024
LoGU: Long-form Generation with Uncertainty Expressions
Ruihan Yang, Caiqi Zhang, Zhisong Zhang +5
While Large Language Models (LLMs) demonstrate impressive capabilities, they still struggle with generating factually incorrect content (i.e., hallucinations). A promising approach…
cs.CL2024
Atomic Calibration of LLMs in Long-Form Generations
Caiqi Zhang, Ruihan Yang, Zhisong Zhang +4
Large language models (LLMs) often suffer from hallucinations, posing significant challenges for real-world applications. Confidence calibration, as an effective indicator of hallu…
cs.CL2024
Conformity in Large Language Models
Xiaochen Zhu, Caiqi Zhang, Tom Stafford +2
The conformity effect describes the tendency of individuals to align their responses with the majority. Studying this bias in large language models (LLMs) is crucial, as LLMs are i…