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Author

Peixuan Han

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#artificial intelligence Preprint Aug 2025

Rethinking Prospect Theory for LLMs: Revealing the Instability of Decision-Making under Epistemic Uncertainty

Real-world decision-making often involves uncertainty expressed in linguistic rather than numerical terms, and Prospect Theory (PT) provides a classic framework for modeling human behavior under such uncertainty. Although recent studies have developed frameworks to estimate PT parameters for Large Language Models (LLMs...

Rui Wang, Qi-Han Lin, Jiayu Liu et al. · 2 citations
#machine learning Preprint Sep 2026

Cliff: Learning Process Rewards from the First Mistake

Cliff, a reward shaping strategy that utilizes an off-the-shelf LLM as a teacher to identify the first mistake in each rollout, is proposed and established as a simple, general and effective approach for improving RLVR with richer, fine-grained supervision.

Pei-Xuan Han, Runnan Wang, Ketan Ramaneti et al. · 1 citation

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