Senyu Fei — accepted AI-conference papers

2026

LIBERO-Plus: A Progressive Robustness Benchmark for Visual-Language-Action Models

Senyu Fei, Siyin Wang, Junhao Shi, Zihao Dai, Jikun Cai, Pengfang Qian +7

CVPR 2026

Visual-Language-Action (VLA) models report impressive success rates exceeding 95% on robotic manipulation benchmarks, yet these results may mask fundamental weaknesses in robustness. Current simulation-based robustness evaluations suffer from narrow perturbation coverage, manual design constraints,

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2026

SRPO: Self-Referential Policy Optimization for Vision-Language-Action Models

Senyu Fei, Siyin Wang, Li Ji, Ao Li, Shiduo Zhang, Liming Liu +4

CVPR 2026

Vision-Language-Action (VLA) models excel in robotic manipulation but are constrained by their heavy reliance on expert demonstrations, leading to demonstration bias and limiting performance. Reinforcement learning (RL) is a vital post-training strategy to overcome these limits, yet current VLA-RL m

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