activity
20192026
most citedFine-Grained Semantically Aligned Vision-Language Pre-Training

29 citations · 116 across the 52 of their papers we have counts for

collaborators

59 papers

cs.CV2026

AVC-Reward: Event-Centric Audio-Video Consistency Evaluation

Yuruo Wu, Kaihang Pan, Kai Shen +6

As joint audio-video generation models become more capable, they can generate audio-visual scenes exhibiting three forms of complexity: multi-event composition, multi-layer audio m…

cs.AI2026

SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments

Yundaichuan Zhan, Minghe Gao, Zhongqi Yue +7

Recent works have explored integrating Vision-Language Models (VLMs) with classical planners that rely on symbolic representations of planning problems to generate long-horizon pla…

cs.CV2026

InstructSAM: Segment Any Instance with Any Instructions

Yuqian Yuan, Wentong Li, Zhaocheng Li +6

In this paper, we introduce InstructSAM, a unified and streamlined framework designed for multi-instance segmentation under arbitrary instructions. We formulates instruction-driven…

cs.AI2026

Learning to Adapt: Self-Improving Web Agent via Cognitive-Aware Exploration

Weile Chen, Bingchen Miao, Qifan Yu +6

Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on handcrafted execution pipelines…

cs.CV2026

SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness

Haiyi Qiu, Kaihang Pan, Jiacheng Li +3

Recent unified image generation models have achieved remarkable success by employing MLLMs for semantic understanding and diffusion backbones for image generation. However, these m…

cs.LG2026

CORE: Code-based Inverse Self-Training Framework with Graph Expansion for Virtual Agents

Keyu Wang, Bingchen Miao, Wendong Bu +7

The development of Multimodal Virtual Agents has made significant progress through the integration of Multimodal Large Language Models. However, mainstream training paradigms face…