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cs.LG2026
PRISM: Preference-Aware Influence Function Based Data Selection Method for Efficient Fine-Tuning
Qihao Lin, Guanxu Chen, Dongrui Liu +1
As LLMs continue to scale up, improving training efficiency heavily relies on effective data utilization. Data selection mitigates this issue by allocating the limited training bud…
cs.LG2025
ExGRPO: Learning to Reason from Experience
Runzhe Zhan, Yafu Li, Zhi Wang +5
Reinforcement learning from verifiable rewards (RLVR) is an emerging paradigm for improving the reasoning ability of large language models. However, standard on-policy training dis…
cs.LG2025★ 1 cited
Rethinking Entropy Regularization in Large Reasoning Models
Yuxian Jiang, Yafu Li, Guanxu Chen +3
Reinforcement learning with verifiable rewards (RLVR) has shown great promise in enhancing the reasoning abilities of large reasoning models (LRMs). However, it suffers from a crit…