collaborators

9 papers

cs.AI2026

Dual Exam: Controlled Evaluation of Multimodal Agents and World Models

Zhefan Rao, Meng Chu, Xuan Zhang +80

World Models (WMs) can support Multimodal Agents (MAs) through simulated experience, while Agent trajectories can inform World Model refinement. Evaluating this interaction require…

cs.RO2026

Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models

Senqiao Yang, Chengyao Wang, Yuxin Chen +13

Scaling robot data is crucial for building generalist Vision-Language-Action (VLA) models, yet robot trajectories are harder to scale than web-scale image-text data because embodie…

cs.CV2026

GKDT: General Keypoint Detection Transformer

Changsheng Lu, Yuxin Chen, Haokun Gui +5

With the emergence of various pre-trained vision and language models, computer vision is shifting from narrow-domain to open-domain recognition. The construction of a more powerful…

cs.CV2026

LCG: Long-Context Consistent Image Generation with Sparse Relational Attention

Zihao Wang, Yijia Xu, Haoze Zheng +3

Recent image generation models achieve impressive quality in single-image synthesis, but often fail to maintain consistency across sequential outputs, as required in comics, storyb…

cs.AI2026

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47

As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…

cs.CV2025

Less Is More, but Where? Dynamic Token Compression via LLM-Guided Keyframe Prior

Yulin Li, Haokun Gui, Ziyang Fan +4

Recent advances in Video Large Language Models (VLLMs) have achieved remarkable video understanding capabilities, yet face critical efficiency bottlenecks due to quadratic computat…

cs.CV2025

VisionDirector: Vision-Language Guided Closed-Loop Refinement for Generative Image Synthesis

Meng Chu, Senqiao Yang, Haoxuan Che +8

Generative models can now produce photorealistic imagery, yet they still struggle with the long, multi-goal prompts that professional designers issue. To expose this gap and better…

cs.SD2025

MGM-Omni: Scaling Omni LLMs to Personalized Long-Horizon Speech

Chengyao Wang, Zhisheng Zhong, Bohao Peng +7

We present MGM-Omni, a unified Omni LLM for omni-modal understanding and expressive, long-horizon speech generation. Unlike cascaded pipelines that isolate speech synthesis, MGM-Om…

cs.CV2025

TraveLLaMA: A Multimodal Travel Assistant with Large-Scale Dataset and Structured Reasoning

Meng Chu, Yukang Chen, Haokun Gui +3

Tourism and travel planning increasingly rely on digital assistance, yet existing multimodal AI systems often lack specialized knowledge and contextual understanding of urban envir…