activity
20242026
collaborators

10 papers

cs.CV2026

Quo Vadis, World Modeling?

Yu Yang, Xuemeng Yang, Licheng Wen +17

Continually improving agents require dynamic interaction feedback beyond static supervision, yet direct real-environment interaction is costly, slow, unsafe, and hard to paralleliz…

cs.CV2026

Beyond Time Shifts: Adapting Omni-LLM as a Reference-Free Evaluator for Generative Audio-Visual Models

Yijie Qian, Juncheng Wang, Chao Xu +6

As audio-visual generative models evolve into world simulators, cross-modal synchronization stands as a critical proxy for assessing the consistency of world dynamics and causality…

cs.CV2026

Progression as Latent Drift: Generative Forecasting of Slow-Evolving Pathologies

Yuxiang Feng, Juncheng Wang, Chao Xu +7

Forecasting the future anatomy of slow-evolving neurodegenerative diseases could enable earlier, more targeted intervention and improve clinical trial design, but it remains challe…

cs.AI2026

Format-Constraint Coupling in Knowledge Graph Construction from Statistical Tables

Jingxuan Qi, Zhiqiang Ye, Yuxiang Feng

An extraction schema should not reduce knowledge graph fidelity. On statistical CSV, however, it can. We study country-by-year time-series matrices, a common layout on open-data po…

cs.CV2026

NEWTON: Agentic Planning for Physically Grounded Video Generation

Yuxiang Feng, Juncheng Wang, Chao Xu +7

Video generation models produce visually compelling results but systematically violate physical commonsense -- on VideoPhy-2, the best model achieves only 32.6% joint accuracy. We…

cs.MA2026

AD-CARE: A Guideline-grounded, Modality-agnostic LLM Agent for Real-world Alzheimer's Disease Diagnosis with Multi-cohort Assessment, Fairness Analysis, and Reader Study

Wenlong Hou, Sheng Bi, Guangqian Yang +16

Alzheimer's disease (AD) is a growing global health challenge as populations age, and timely, accurate diagnosis is essential to reduce individual and societal burden. However, rea…