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cs.CV2026

H-OPD: Confidence Aware Heterogeneous Multi-Teacher Multimodal On-policy Distillation

Qixiang Yin, Huanjin Yao, Yuchen Cai +5

On-policy distillation (OPD) has recently emerged as an effective post-training paradigm by providing supervision on student-generated trajectories. However, existing OPD methods f…

cs.CV2026

Improving Vision-language Models with Perception-centric Process Reward Models

Yingqian Min, Kun Zhou, Yifan Li +6

Recent advancements in reinforcement learning with verifiable rewards (RLVR) have significantly improved the complex reasoning ability of vision-language models (VLMs). However, it…

cs.CV2026

MM-DeepResearch: A Simple and Effective Multimodal Agentic Search Baseline

Huanjin Yao, Qixiang Yin, Min Yang +5

We aim to develop a multimodal research agent capable of explicit reasoning and planning, multi-tool invocation, and cross-modal information synthesis, enabling it to conduct deep…

cs.CV2026

Beyond the Last Frame: Process-aware Evaluation for Generative Video Reasoning

Yifan Li, Yukai Gu, Yingqian Min +6

Recent breakthroughs in video generation have demonstrated an emerging capability termed Chain-of-Frames (CoF) reasoning, where models resolve complex tasks through the generation…

cs.CV2025

R1-ShareVL: Incentivizing Reasoning Capability of Multimodal Large Language Models via Share-GRPO

Huanjin Yao, Qixiang Yin, Jingyi Zhang +8

In this work, we aim to incentivize the reasoning ability of Multimodal Large Language Models (MLLMs) via reinforcement learning (RL) and develop an effective approach that mitigat…