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cs.CL2024
Confidence Calibration and Rationalization for LLMs via Multi-Agent Deliberation
Ruixin Yang, Dheeraj Rajagopal, Shirley Anugrah Hayati +2
Uncertainty estimation is a significant issue for current large language models (LLMs) that are generally poorly calibrated and over-confident, especially with reinforcement learni…
cs.CL2024★ 2 cited
Under the Surface: Tracking the Artifactuality of LLM-Generated Data
Debarati Das, Karin De Langis, Anna Martin-Boyle +14
This work delves into the expanding role of large language models (LLMs) in generating artificial data. LLMs are increasingly employed to create a variety of outputs, including ann…