Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs
Reinforcement learning with metacognitive feedback and metacognitive data selection improve large language model calibration by enabling accurate self-assessment of performance and…
Hugging Face · Daily Papers
·Gabrielle Kaili-May Liu, Avi Caciularu
·
·▲ 16 upvotes
Este artigo está em destaque na seleção diária de papers do Hugging Face, curada pela comunidade de pesquisa em IA.
Autores: Gabrielle Kaili-May Liu, Avi Caciularu, Gal Yona, Idan Szpektor, Arman Cohan
- 16 upvotes da comunidade
- Temas: reinforcement learning, metacognitive feedback, metacognitive data selection, faithful calibration, self-reported confidence scores, intrinsic uncertainty
Resumo
Resumo original (em inglês), extraído do paper:
Reinforcement learning with metacognitive feedback and metacognitive data selection improve large language model calibration by enabling accurate self-assessment of performance and uncertainty.Onde ler
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