arXiv AI July 29, 2026 By Yiteng Tu, Weihang Su, Zitao Su, Yiqun Liu, Min Zhang, Qingyao Ai

Structure-aware Relative Policy Optimization for Ranking

arXiv:2607. 25268v1 Announce Type: cross Abstract: Ranking is a fundamental component of modern information access systems.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

reinforcement-learning

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RankBuffer: Efficient Ranking-Based Rewards for Open-Ended Generation

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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction

arXiv:2608. 06310v1 Announce Type: new Abstract: Recent advances in reward modeling show a paradigm shift from discriminative reward models to generative reward models.

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llms reinforcement-learning benchmarks

arXiv Machine Learning

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Efficient Offline Learning of Ranking Policies via Top-$k$ Policy Decomposition

arXiv:2609.36740v1 Announce Type: new Abstract: Many recommender systems such as for e-commerce and news platforms aim to provide users with rankings they are likely to interact with. Off-Policy Lear...

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arXiv Machine Learning

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RLVR$^{2}$: Reinforcement Learning with Verifiable Rubric-based Ranking

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arXiv AI

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Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning

arXiv:2604. 02091v2 Announce Type: replace-cross Abstract: Rerankers play a pivotal role in refining retrieval results for Retrieval-Augmented Generation.

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