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cs.CV2026
OmniReasoner: Thinking with Long Audio-Video via Native Tool Use
Yu Chen, Caorui Li, Ziyu Xiong +8
Long audio-video reasoning is difficult for omnimodal LLMs because the decisive evidence is often sparse, cross-modal, and too expensive to preserve with uniformly high-fidelity in…
cs.CV2026
Claim-Level Rubric Rewards for Video Caption Reinforcement Learning
Mingqi Gao, Hongyuan Dong, Yifei Chen +6
In this paper, we introduce Claim-Level Rubric Rewards (CuRe), a structured reward framework designed to address the reward-design bottleneck in reinforcement learning for dense vi…