arXiv AI September 17, 2026 By Xinxin Song, Siyuan Li, Tingxiong Xiao, Jinli Suo

Anchoring What Matters: A Dual-Level Learning Framework for Visually-Grounded Multimodal Reasoning

The paper introduces PIVOT, a dual-level learning framework designed to improve visually-grounded multimodal reasoning in large vision-language models. PIVOT employs a self‑calibrated experience replay mechanism to selectively reuse valuable visual reasoning trajectories, and a vision‑guided advantage allocation scheme that assigns extra rewards to tokens with strong visual support. Experiments on multiple benchmarks show that PIVOT enhances the multimodal reasoning performance of these models.

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