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#artificial intelligence Preprint Oct 2026

ProAS: A Progress-Aware Advantage Shaping Framework for Multi-Turn Agentic Reinforcement Learning

Progress-Aware Advantage Shaping (ProAS) is proposed, a plug-and-play framework that leverages a dynamically evolving Agentic Reference Graph (ARG) to achieve fine-grained credit assignment via Masking Unreasonable Incentives (MUI) and Asymmetric Penalty Redistribution (APR).

Bowen Ding, Ming-Da Wan, Yu-Han Chen et al. · 0 citations
#natural language process... Preprint Oct 2026

HARPO: Hallucination-Aware Reinforcement Learning for Faithful and Creative Language Generation

Large Language Models (LLMs) are prone to generating hallucinated content, which compromises their reliability in knowledge-intensive tasks. To address this challenge without sacrificing creativity, we propose HARPO, a reinforcement learning framework designed to jointly optimize faithfulness and creativity. HARPO inco...

Tie-Zheng Yu, Yu-Xin Jiang, Jin-Peng Li et al. · 0 citations

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