collaborators

15 papers

cs.CV2026

GUI-AC: Enhancing Continual Learning in GUI Agents

Can Lin, Tao Feng, Hangjie Yuan +3

Graphical User Interfaces (GUIs) serve as the dominant medium for human-computer interaction, yet building GUI agents that generalize across the vast diversity of real-world interf…

cs.CV2026

Lumos-Nexus: Efficient Frequency Bridging with Homogeneous Latent Space for Video Unified Models

Jiazheng Xing, Hangjie Yuan, Lingling Cai +9

Connector-based video unified models have demonstrated strong capability in instruction-grounded video synthesis, but integrating a large high-fidelity generator into the unified t…

cs.CV2026

5% > 100%: Flatness Preference is All You Need for Multimodal Parameter-Efficient Fine-Tuning

Yifan Zhu, Can Lin, Hangjie Yuan +4

Parameter-Efficient Fine-Tuning (PEFT) methods provide a streamlined and efficient tool for adapting large models to domain-specific multimodal downstream tasks. Although these met…

cs.LG2026

Filter, Then Reweight: Rethinking Optimization Granularity in On-Policy Distillation

Yuying Li, Leqi Zheng, Yongzi Yu +6

On-Policy distillation (OPD) in large language models is shifting from full-trace KL supervision toward more selective training paradigms. Recent OPD methods increasingly focus on…

cs.CV2026

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems

Shuhang Chen, Hangjie Yuan, Yunqiu Xu +5

Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially in reliably perceiving and inte…

cs.LG2026

A Faster Path to Continual Learning

Wei Li, Hangjie Yuan, Zixiang Zhao +3

Continual Learning (CL) aims to train neural networks on a dynamic stream of tasks without forgetting previously learned knowledge. Among optimization-based approaches, C-Flat has…