Author

Kaiyan Zhang

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#artificial intelligence Review Open access Oct 2026

Reinforcement Learning-driven Diffusion Models: Language, Vision, and Beyond.

Diffusion models (DMs) have steadily demonstrated outstanding performance in high-fidelity, controllable generation across diverse scenarios, following the "pretraining-finetuning" paradigm established in LLMs. Despite these advances, conventional DMs still face critical limitations in sophisticated reasoning, autonomo...

Zhi-Yuan Ma, Jia-Bao Wei, Tian-Yu Wang et al. · IEEE Transactions on Pattern... · 0 citations

Preprint Sep 2026

Unified Trajectory Matching Policy Optimization: Diverse T2I Generation and VLA Generalization

Reward-maximizing reinforcement learning (RL) is widely used to post-train stochastic diffusion and flow policies for text-to-image (T2I) generation. However, reward-maximizing RL causes policy mode collapse even under reference KL or entropy regularization, reducing the policy to a single high-reward mode. In T2I, thi...

Zhi-Yuan Ma, Jia-Ming Li, Ling-Zhen Li et al. · 0 citations

Jul 2026

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

OpenMLE is introduced, an open full-stack system for RSI research in MLE, spanning verifiable task environments with execution feedback, operator learning, and long-horizon search (OpenMLE-Evo) and enabling reproducible research on executable AI4AI toward RSI.

Junlin Yang, Che Jiang, Yu Fu et al. · arXiv.org · 7 citations