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cs.RO2026
Trusting Imagined Futures: Auditing Imagined Rewards for VLA Post-Training
Zicheng Kong, Zhenbo Xu, Haoyan Zhang +7
Video world models enable candidate actions to be evaluated through imagined outcomes, but high predicted rewards can favor trajectories with poor execution quality. We introduce T…
cs.CL2026
Omni-RRM: Advancing Omni Reward Modeling via Automatic Rubric-Grounded Preference Synthesis
Zicheng Kong, Dehua Ma, Zhenbo Xu +9
Multimodal large language models (MLLMs) struggle with alignment due to the limitations of existing reward models (RMs), which are predominantly vision-centric, dependent on costly…