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arXiv Computer Vision By Raja Kumar, Rajat Koner, Ritwick Chaudhry, Zhuowei Li, Nishant Sankaran, Yifan Xing

SPLIT-RL: Staged Perception-Language Reasoning Training with Claim-Level Advantages

Read the original on arXiv Computer Vision →

SPLIT-RL introduces a staged post‑training method that separates visual reasoning (VR) and language reasoning (LR) into distinct phases, allowing each phase to be optimized with a phase‑specific reward. The approach includes Claim‑Level Advantage (CLA‑GRPO), which breaks VR rollouts into atomic visual claims and assigns fine‑grained advantages based on visual‑type group formation. Experiments on Qwen3‑VL and InternVL models show that SPLIT‑RL improves average accuracy by 1.4–6.1 points over GRPO and enhances both VR and LR capabilities.

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