collaborators

20 papers

cs.LG2026

Diagnosing and Mitigating Perception-Decision Misalignment in Omni-LLMs via Modality Subspace Activation

Hongbo Jiang, Jie Li, Yunhang Shen +2

Omni-Large Language Models (Omni-LLMs) power complex multi-modal reasoning in applications like World Action Models and autonomous agents. However, their strong performance often m…

cs.CV2026

Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion

Lijiang Li, Zuwei Long, Yunhang Shen +6

While recent multimodal large language models (MLLMs) have made impressive strides, they predominantly employ a conventional autoregressive architecture as their backbone, leaving…

cs.CV2026

SMART: Shot-Aware Multimodal Video Moment Retrieval with Audio-Enhanced MLLM

An Yu, Weiheng Lu, Jian Li +4

Video Moment Retrieval is a task in video understanding that aims to localize a specific temporal segment in an untrimmed video based on a natural language query. Despite recent pr…

cs.CV2026

Toward Native Multimodal Modeling: A Roadmap

Siyu An, Junru Lu, Junnan Dong +18

Multimodal modeling represents a vital step from modality-agnostic reasoning toward world modeling. While early approaches predominantly rely on late-fusion that assembles encoders…

cs.CL2026

GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistant

Zhuokang Shen, Yifan Wang, Hanyu Chen +6

Recent advances in large language models (LLMs) have enabled increasingly capable chatbots. However, most existing systems focus on single-user settings and do not generalize well…

cs.CV2026

Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding

Chaoyou Fu, Haozhi Yuan, Yuhao Dong +16

With the rapid advancement of video understanding, existing benchmarks are becoming increasingly saturated, exposing a critical discrepancy between inflated leaderboard scores and…