activity
20242026
most citedSVGen: Interpretable Vector Graphics Generation with Large Language Models

4 citations · 11 across the 25 of their papers we have counts for

collaborators

27 papers

cs.CV2026

Semantic-Aware Temporal Adaptation for UAV Anti-UAV Tracking

Xiaozhen Qiao, Da Zhang, Yubin Guo +3

UAV Anti-UAV tracking is an emerging low-altitude security task for localizing an adversarial UAV using the onboard camera of a moving observer UAV. It differs from conventional UA…

cs.CV2026

An Open-Source Benchmark and Baseline for Multi-temporal Referring Segmentation

Bingyu Li, Da Zhang, Tao Huo +3

Large Vision-Language Models (LVLMs) have shown strong visual understanding and language-guided grounding abilities, yet their capacity for multi-temporal visual reasoning remains…

cs.LG2026

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

Da Zhang, Bingyu Li, Zhiyuan Zhao +3

Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existing methods struggle to jointl…

cs.LG2026

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

Yicheng Zou, Dongsheng Zhu, Lin Zhu +174

We introduce Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model. Scaling to this unprecedented size, the model delivers a comprehensive enhancem…

cs.CV2026

Towards Realistic Open-Vocabulary Remote Sensing Segmentation: Benchmark and Baseline

Bingyu Li, Tao Huo, Haocheng Dong +4

Open-vocabulary remote sensing image segmentation (OVRSIS) remains underexplored due to fragmented datasets, limited training diversity, and the lack of evaluation benchmarks that…

cs.CV2026

Boosting Quantitive and Spatial Awareness for Zero-Shot Object Counting

Da Zhang, Bingyu Li, Feiyu Wang +2

Zero-shot object counting (ZSOC) aims to enumerate objects of arbitrary categories specified by text descriptions without requiring visual exemplars. However, existing methods ofte…