Author

He-Nan Sun

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#artificial intelligence Preprint Sep 2026

DCRL: Decoupling and Coupling Reinforcement Learning via Policy-Reward Manifold Alignment

Reinforcement learning (RL) has emerged as a key paradigm for improving the reasoning capabilities of large language models (LLMs). However, existing reward systems, such as rule-based and reward-model-based, often exhibit issues such as unstable optimization and reward hacking. In this work, we revisit the general rea...

He-Nan Sun, Ze-Hua Li, Hai-Tao Hu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

PhyMo: A Physical-Field Modality for Multimodal AI4Physics

Experiments on five datasets spanning diverse physical environments show that PhyMo achieves state-of-the-art performance, compared to the strongest baseline on each dataset, demonstrating the superiority of PhyMo on multimodal representation learning in AI4Physics.

He-Nan Sun, Hai-Tao Hu, Jin Liu et al. · 0 citations