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P. Jenkins

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#artificial intelligence Preprint Sep 2026

Rethinking Training-Inference Mismatch in LLM Reinforcement Learning: Where It Arises and How to Correct It

CIS replaces the unbounded second moment that governs the error of exact importance sampling with a term bounded by a constant, at the cost of a bias controlled by the truncated excess, in evaluation across three mixture-of-experts models and five mathematical reasoning benchmarks.

Tian-Run Yu, Kai-Xiang Zhao, Shang-Zhe Li et al. · 0 citations
#artificial intelligence Preprint May 2026

Self-Correction Can Amplify Hallucinations: Fact-Level Repair with Graph-Based Evidence Routing in Multimodal Generation

TIGER is presented, an inference-time framework that redesigns feedback for localized repair that reduces unsupported content while preserving task quality and a CrisisFACTS case study suggests that the same repair mechanism can improve grounding in multi-source settings.

Kaixiang Zhao, Tianrun Yu, Shawn Huang et al. · 0 citations

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