Author

Jiaxuan Luo

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#artificial intelligence Preprint Oct 2026

CriticHack: Evaluating Visual Rewards Under Robot Policy Optimization

Learned visual reward models are increasingly used to optimize robot policies, yet a reward model can score an execution that acts on the wrong object as highly as one that completes the task. We show that optimizing such a reward can amplify these wrong-object failures while reward and task success both rise, so the s...

Jia-Xuan Luo, Xing-Guo Xu, Shan-Shan Wang et al. · 0 citations

Jul 2026

ExpertVerse: A General-Purpose Benchmark for Expert-Level Reasoning in Knowledge-Intensive Visual Synthesis

A tailored Bootstrapped Pareto Policy Optimization (BPPO) is proposed, which synergizes Bootstrapping Reward Rectification and Conflict-Aware Pareto Advantage Fusion (CPAF) and exposes critical reasoning deficits, highlighting imperative for knowledge-intensive benchmarks towards next-generation visual generation.

Yuan Wang, Yongchao Du, Mengting Chen et al. · arXiv.org · 1 citation