papers

Publications (9)

cs.AI2025

AI for Service: Proactive Assistance with AI Glasses

Zichen Wen, Yiyu Wang, Chenfei Liao +10

In an era where AI is evolving from a passive tool into an active and adaptive companion, we introduce AI for Service (AI4Service), a new paradigm that enables proactive and real-t…

cs.CV2026

VideoCoCo: Code-as-CoT for Physically-Consistent Video Generation via an Agentic Dual-Engine System

Haodong Li, Tianfei Ren, Xiaoxiao Ma +25

The paper presents VideoCoCo, a system that generates physically consistent videos by having a coding agent produce executable Blender code that defines the scene and its dynamics,…

#text-to-video generation#physically consistent dynamics#code as chain of thought#agentic dual-engine
cs.CV2026

Accelerating Streaming Video Large Language Models via Hierarchical Token Compression

Yiyu Wang, Xuyang Liu, Xiyan Gui +5

Streaming Video Large Language Models (VideoLLMs) have demonstrated impressive performance across various video understanding tasks, but they face significant challenges in real-ti…

cs.CV2026

Flash-Unified: A Training-Free and Task-Aware Acceleration Framework for Native Unified Models

Junlong Ke, Zichen Wen, Boxue Yang +6

Native unified multimodal models, which integrate both generative and understanding capabilities, face substantial computational overhead that hinders their real-world deployment.…

cs.CV2026

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing

Zebang Cheng, Shuimu Chen, Boxue Yang +7

Reinforcement learning for multimodal large language models (MLLMs) is often hindered by severe reward sparsity in complex reasoning tasks. This challenge is particularly pronounce…

cs.CV2026

EvoStreaming: Your Offline Video Model Is a Natively Streaming Assistant

Zichen Wen, Boxue Yang, Junlong Ke +5

Streaming video understanding demands more than watching longer videos: assistants must decide when to speak in real time, balancing responsiveness against verbosity. Yet most vide…

cs.LG2026

ASPECT: Node-Level Adaptive Spectral Fusion for Graph Contrastive Learning

Zhuolong Li, Boxue Yang, Haopeng Chen

Spectral graph contrastive learning often constructs low- and high-frequency views to capture complementary graph signals, but these views are commonly combined by graph-level or n…

cs.CV2026

Innovator-VL: A Multimodal Large Language Model for Scientific Discovery

Zichen Wen, Boxue Yang, Shuang Chen +30

We present Innovator-VL, a scientific multimodal large language model designed to advance understanding and reasoning across diverse scientific domains while maintaining excellent…

cs.CV2026

4DVLT: Dynamic Scene Understanding with Worldline-Centered Vision-Language Tracking

Chaoyue Li, Boxue Yang, Shengyao Zhou +3

4D dynamic scene understanding requires grounding language to a persistent worldline that binds identity, metric 3D motion, and synchronized multi-view 2D projections. Existing par…