activity
20242026
collaborators

7 papers

cs.CV2026

SymRegFlow: Symmetry-Regularized Flow Matching for Video World Models

Xi Ye, Yuzhu Wang, Xiaoyang Liu +6

Flow-matching-based multi-view world models generate realistic videos, but are commonly restricted to fixed camera rigs. Extending them to continuously varying camera poses require…

cs.CV2026

Task-State Adaptation with Prototype Memory for Multi-Task Dense Prediction

Yangyang Xu, Haobo Yuan, Yuzhu Wang +4

Vision foundation backbones provide strong representations for dense prediction, yet a single shared feature still needs to support tasks with different, image-dependent adaptation…

cs.CV2026

SHIFT: Motion Alignment in Video Diffusion Models with Adversarial Hybrid Fine-Tuning

Xi Ye, Wenjia Yang, Yangyang Xu +4

Image-conditioned video diffusion models achieve impressive visual realism but often suffer from weakened motion fidelity, e.g., reduced motion dynamics or degraded long-term tempo…

cs.AI2025

MaLoRA: Gated Modality LoRA for Key-Space Alignment in Multimodal LLM Fine-Tuning

Xinhan Zheng, Huyu Wu, Xueting Wang +2

Multimodal large language models (MLLMs) exhibit a pronounced preference for textual inputs when processing vision-language data, limiting their ability to reason effectively from…

cs.LG2025

Diffusion Models as Dataset Distillation Priors

Duo Su, Huyu Wu, Huanran Chen +4

Dataset distillation aims to synthesize compact yet informative datasets from large ones. A significant challenge in this field is achieving a trifecta of diversity, generalization…

cs.CV2025

Multi-Task Dense Prediction Fine-Tuning with Mixture of Fine-Grained Experts

Yangyang Xu, Xi Ye, Duo Su

Multi-task learning (MTL) for dense prediction has shown promising results but still faces challenges in balancing shared representations with task-specific specialization. In this…

cs.CV2024

Towards Unifying Understanding and Generation in the Era of Vision Foundation Models: A Survey from the Autoregression Perspective

Shenghao Xie, Wenqiang Zu, Mingyang Zhao +6

Autoregression in large language models (LLMs) has shown impressive scalability by unifying all language tasks into the next token prediction paradigm. Recently, there is a growing…