activity
20242026
most citedDownstream-Pretext Domain Knowledge Traceback for Active Learning

3 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Terminal-Universe: Turning Agent Trajectories into Scalable Terminal Environments

Jie Wu, Zhenru Zhang, Beichen Zhang +11

As terminal-based code agents become prevalent, agent trajectories have accumulated at scale, while realistic, executable environments remain scarce. However, environments are what…

cs.CV2026

DyGT: Modeling Object Dynamics with 3D Gaussian Temporal-Spatial Particle Graph Transformer

Yansong Wang, Zhaobo Qi, Xinyan Liu +4

Modeling object dynamics from limited visual observations is a fundamental problem for enabling accurate motion trajectory prediction in embodied interaction scenarios. Existing dy…

cs.LG2026

SEE: Structure-aware Exploring & Exploiting for Long-horizon GUI Agent Trajectory Synthesis

Zhuohang Fan, Beichen Zhang, Yuanfa Li +4

Graphical User Interface (GUI) agents powered by vision-language models hold promise for automating real-world mobile tasks. However, progress is limited by the lack of high-covera…

cs.CV2026

STAND: Semantic Anchoring Constraint with Dual-Granularity Disambiguation for Remote Sensing Image Change Captioning

Yanpei Gong, Beichen Zhang, Hao Wang +5

Remote sensing image change captioning (RSICC) aims to describe the difference between two remote sensing images. While recent methods have explored video modeling, they largely ov…

cs.CV2025

Masked Temporal Interpolation Diffusion for Procedure Planning in Instructional Videos

Yufan Zhou, Zhaobo Qi, Lingshuai Lin +5

In this paper, we address the challenge of procedure planning in instructional videos, aiming to generate coherent and task-aligned action sequences from start and end visual obser…

cs.LG2024★ 3 cited

Downstream-Pretext Domain Knowledge Traceback for Active Learning

Beichen Zhang, Liang Li, Zheng-Jun Zha +2

Active learning (AL) is designed to construct a high-quality labeled dataset by iteratively selecting the most informative samples. Such sampling heavily relies on data representat…