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From the 1 of 7 linked papers with an AI index.

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7 papers

cs.LG2026

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation

Yifan Ding, Xincheng Wei, Yoshua Y. Li +7

Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) scores each token against a stron…

cs.CV2026

FaithEyes: Towards Faithful Tool Use via Multi-Agent Process-Image Verification

Haoqing Wang, Xingrun Xing, Wei Xia +2

FaithEyes proposes a multi‑agent framework where a vision‑language model judges its own tool calls to ensure they are useful, improving both accuracy and tool faithfulness on visua…

cs.LG2026

Trust Region On-Policy Distillation

Xingrun Xing, Haoqing Wang, Boyan Gao +2

On-Policy Distillation (OPD) is a fundamental technique for efficient post-training of large language models (LLMs), with broad applications in agent learning, multi-task enhanceme…

cs.CL2026

Outcome-Grounded Advantage Reshaping for Fine-Grained Credit Assignment in Mathematical Reasoning

Ziheng Li, Liu Kang, Feng Xiao +7

Group Relative Policy Optimization (GRPO) has emerged as a promising critic-free reinforcement learning paradigm for reasoning tasks. However, standard GRPO employs a coarse-graine…

cs.CL2026

MemTrain: Self-Supervised Context Memory Training

Ziheng Li, Xingrun Xing, Haoqing Wang +2

Memory is an indispensable capability for long-horizon LLM agents, enabling them to preserve and utilize information accumulated across extended interactions. Existing memory-agent…

cs.LG2026

IRPM: Intergroup Relative Preference Modeling for Pointwise Generative Reward Models

Haonan Song, Qingchen Xie, Huan Zhu +12

Generative Reward Models (GRMs) have demonstrated strong performance in reward modeling, due to their interpretability and potential for refinement through reinforcement learning (…