Author

Yi-Lun Kong

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Preprint Sep 2026

PF-RL: Progress Field Reinforcement Learning via Goal-Conditioned Value Geometry for Vision-Language-Action Models

Reinforcement Fine-Tuning~(RFT) has emerged as a promising paradigm for improving Vision-Language-Action~(VLA) policies, yet sparse task-level outcomes provide limited credit for intermediate transitions, especially in long-horizon manipulation. A natural approach is to model intermediate task progress and use it as de...

Yun-Peng Qing, Yi-Lun Kong, Si-Xu Lin et al. · 0 citations

Jul 2026

ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI

ACE-Brain-0.5 is presented, a unified embodied foundation model that organizes robot intelligence into five coupled functions: spatial perception, decision making, embodied interaction, self-monitoring, and self-improvement, and SSR+, which extends Scaffold-Specialize-Reconcile with a Reactivate stage after task-vector...

Zi-Yang Gong, Hao-Ming Gu, Ze-Hang Luo et al. · arXiv.org · 3 citations

Preprint Jul 2026

ExToken: Structured Exploration for Efficient Vision-Language-Action Reinforcement Fine-tuning

ExToken is introduced, a simple yet general framework that condition VLA policies on discrete behavioral priors derived from offline demonstrations for structured exploration that consistently accelerates convergence, improves task performance, and exhibits strong robustness under highly constrained interaction budgets...

Yilun Kong, Yunpeng Qing, Guozheng Ma et al. · 0 citations