arxiv
PublishedJune 24, 2026 at 4:00 AM
—neutral
KLip-PPO: A per-sample KL perspective on PPO-Clip
Publisher summary· verbatim
arXiv:2606.23932v1 Announce Type: new Abstract: Proximal Policy Optimization (PPO) is the standard policy-gradient algorithm for on-policy reinforcement learning. The literature presents it in two forms, a clipped surrogate that bounds the importance ratio between successive policies and a Kullback-
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivCulturalMenuBench: Probing the Knowledge-Application Gap in Multimodal Culinary Reasoning4harxivProactive Service Agents: A Unified Decision Framework, Methods, and Evaluation4harxivX-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System4harxivA Blind Trust, the Bloody Thrust: When Attacker-Controlled Hook Updates Steer AI Agent Harnesses towards Malicious Behaviors4hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗