collaborators

11 papers

cs.CV2026

3D-Aware VLMs with Implicit and Explicit Geometries

Wenhao Li, Xueying Jiang, Quanhao Qian +4

Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that require fine-grained spatial unde…

cs.CV2026

From Fixed to Free Cameras: Calibration-Free View-Robust Vision-Language-Action Model

Wenhao Li, Xueying Jiang, Quanhao Qian +4

Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios. Existing vie…

cs.CV2026

A Comprehensive Study on Visual Token Redundancy for Discrete Diffusion-based Multimodal Large Language Models

Duo Li, Zuhao Yang, Xiaoqin Zhang +2

Discrete diffusion-based multimodal large language models (dMLLMs) have emerged as a promising alternative to autoregressive MLLMs thanks to their advantages in parallel decoding a…

cs.CV2026

Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

Keming Wu, Zuhao Yang, Kaichen Zhang +24

Recent visual generation models have made major progress in photorealism, typography, instruction following, and interactive editing, yet they still struggle with spatial reasoning…

cs.CV2026

ParaVT: Taming the Tool Prior Paradox for Parallel Tool Use in Agentic Video Reinforcement Learning

Zuhao Yang, Kaichen Zhang, Sudong Wang +7

Training large multimodal models (LMMs) via reinforcement learning (RL) to natively invoke video-processing tools (e.g., cropping) has become a promising route to long-video unders…

cs.CV2026

LongVT: Incentivizing "Thinking with Long Videos" via Native Tool Calling

Zuhao Yang, Sudong Wang, Kaichen Zhang +8

Large multimodal models (LMMs) have shown great potential for video reasoning with textual Chain-of-Thought. However, they remain vulnerable to hallucinations, especially when proc…