arXiv Machine Learning
Jul 22
Exposure-Based Reinforcement Learning to Rank
arXiv:2607. 18689v1 Announce Type: new Abstract: Reinforcement learning (RL) methods for learning-to-rank (LTR) can optimize (almost) any ranking goal, e.
Exposure-Based Reinforcement Learning to Rank
Reinforcement learning (RL) methods for learning-to-rank (LTR) can optimize (almost) any ranking goal, e. g.
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RRC: Unlocking Generative Reward Models in LLM Reinforcement Learning via Ranking-Based Reward Construction
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Uncovering and Mitigating Aggregation-Induced Reward Hacking in Multi-Reward Reinforcement Learning
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arXiv AI
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Selective Timestep Weighting and Advantage-Based Replay for Sample-Efficient Diffusion RLHF
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RLVR$^{2}$: Reinforcement Learning with Verifiable Rubric-based Ranking
Reinforcement Learning with Verifiable Rewards (RLVR) is expanding from tasks with well-defined correctness signals, such as mathematics and code, toward multifaceted quality requirements specified by...
arXiv AI
Jul 7
RSPO: Reward-Swap Policy Optimization for Multi-Turn LLM Agents
arXiv:2607. 04713v1 Announce Type: cross Abstract: Reinforcement learning holds significant potential for training large language models (LLMs) to handle multi-turn interactive tasks.
arXiv AI
Jun 3
Efficient Hyperparameter Optimization for LLM Reinforcement Learning
arXiv:2606. 03073v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is highly sensitive to hyperparameter configurations, making hyperparameter optimization (HPO) essential yet computationally expensive.
arXiv AI
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sGPO: Trading Inference FLOPs for Training Efficiency in RLVR
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Efficient Offline Learning of Ranking Policies via Top-$k$ Policy Decomposition
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arXiv AI
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