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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

SGG-R: From Next-Token Prediction to End-to-End Unbiased Scene Graph Generation

Jiaye Feng, Qixiang Yin, Yuankun Liu +2

Scene Graph Generation (SGG) structures visual scenes as graphs of objects and their relations. While Multimodal Large Language Models (MLLMs) have advanced end-to-end SGG, current…

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.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…

cs.CV2025

Rethinking Two-Stage Referring-by-Tracking in Referring Multi-Object Tracking: Make it Strong Again

Weize Li, Yunhao Du, Qixiang Yin +2

Referring Multi-Object Tracking (RMOT) aims to track multiple objects specified by natural language expressions in videos. With the recent significant progress of one-stage methods…