collaborators

5 papers

cs.CV2026

TimeThink: Reasoning with Time for Video LLMs

Handong Li, Longteng Guo, Zikang Liu +8

Video reasoning requires models to identify and verify temporally localized evidence within long video sequences. Recent Video Large Language Models (Video-LLMs) have shown promisi…

cs.CV2026

Clearer Sight, Fewer Lies: Oriented Pickup Preference Optimization for Multimodal Hallucination Mitigation

Xin Zou, Haolin Deng, Yibo Yan +5

Multimodal Large Language Models (MLLMs) are prone to hallucination as their generation preferences are insufficiently calibrated to visual evidence, causing them to fall back on l…

cs.CV2026

Consistency as Inductive Bias: Learning Cross-View Invariance for Robust Multimodal Reasoning

Xin Zou, Haolin Deng, Yibo Yan +6

Inductive biases steer learning toward generalizable solutions by encoding task structure. In this work, we identify a crucial missing bias in MLLMs: cross-view consistency, \texti…

cs.LG2026

Stabilizing On-Policy Distillation for MLLM Reasoning with Global Normalization

Dongze Hao, Zhiwei Jin, Chen Chen +1

On-policy distillation (OPD) has recently emerged as an important post-training paradigm. By using a stronger teacher model to provide dense, fine-grained supervision for sampled t…

cs.CV2025

AndesVL Technical Report: An Efficient Mobile-side Multimodal Large Language Model

Zhiwei Jin, Xiaohui Song, Nan Wang +36

In recent years, while cloud-based MLLMs such as QwenVL, InternVL, GPT-4o, Gemini, and Claude Sonnet have demonstrated outstanding performance with enormous model sizes reaching hu…