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Rethinking Groups in Critic-Free RLVR

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arXiv:2606. 17250v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a central paradigm for post-training large language models.

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Authors: Yihong Wu, Liheng Ma, Lingfeng Xiao, Muzhi Li, Xinyu Wang, Yingxue Zhang, Jian-Yun Nie
Released: 2026-06-17 (22d ago)
Topic: Related to current project
Relation to my work: Read next because Rethinking Groups in Critic-Free RLVR overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: strong, under, token, line, rate, language, model. Source: arxiv cs.LG (Machine Learning).
arXiv: 2606.17250

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