activity
20222026
most citedMulti-weather Cross-view Geo-localization Using Denoising Diffusion Models

22 citations · 61 across the 32 of their papers we have counts for

collaborators

48 papers

cs.CV2026

Modularized Dynamic-Granularity Video LLM for Multi-Event Long Video Understanding

Wei Feng, Xin Wang, Yu-Wei Zhan +2

Video Large Language Models (Video LLMs) have made significant advancements in various video understanding tasks. However, long-video scenarios remain challenging due to the tensio…

cs.CV2026

Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models

Xin Wang, Wenxuan Liu, Tongtong Feng +1

Large-scale video generation models are increasingly described as world models because they can learn rich spatiotemporal regularities from visual data. However, we argue that an i…

cs.LG2026

OOD-GraphLLM: Graph Large Language Model for Out-of-Distribution Generalized Drug Synergy Prediction

Xin Wang, Linxin Xiao, Yang Yao +1

Drug synergy prediction (DSP) aims to identify efficacious drug combinations under various cellular contexts with different targets. However, the continual emergence of novel compo…

cs.RO2026

WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform

Yu Shang, Yinzhou Tang, Yiding Ma +22

World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about environmental dynamics. However, ex…

cs.LG2026

A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning

Haibo Chen, Xin Wang, Jiaheng Chao +2

Leveraging Graph Neural Networks (GNNs) as graph encoders and aligning the resulting representations with Large Language Models (LLMs) through alignment instruction tuning has beco…

cs.LG2026

Agentic AIs Are the Missing Paradigm for Out-of-Distribution Generalization in Foundation Models

Xin Wang, Haibo Chen, Wenxuan Liu +1

Foundation models (FMs) are increasingly deployed in open-world settings where distribution shift is the rule rather than the exception. The out-of-distribution (OOD) phenomena the…