activity
20222026
most citedPro-tuning: Unified Prompt Tuning for Vision Tasks

2 citations · 4 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

ViTexSZ: Heterogeneous Vision-Text Knowledge Distillation for EEG Seizure Detection

Chenxi Liu, Mingzhao Li, Yicong Liu +4

Automated seizure detection from electroencephalography (EEG) is essential for continuous neurological monitoring, particularly for subclinical epileptic seizures that may exhibit…

cs.AI2025

PDE-Agent: A toolchain-augmented multi-agent framework for PDE solving

Jianming Liu, Ren Zhu, Jian Xu +4

Solving Partial Differential Equations (PDEs) is a cornerstone of engineering and scientific research. Traditional methods for PDE solving are cumbersome, relying on manual setup a…

cs.CV2025

AddressVLM: Cross-view Alignment Tuning for Image Address Localization using Large Vision-Language Models

Shixiong Xu, Chenghao Zhang, Lubin Fan +5

Large visual language models (LVLMs) have demonstrated impressive performance in coarse-grained geo-localization at the country or city level, but they struggle with fine-grained s…

cs.CL2024

Rethinking Comprehensive Benchmark for Chart Understanding: A Perspective from Scientific Literature

Lingdong Shen, Qigqi, Kun Ding +2

Scientific Literature charts often contain complex visual elements, including multi-plot figures, flowcharts, structural diagrams and etc. Evaluating multimodal models using these…

cs.CV2024★ 1 cited

A Survey of Low-shot Vision-Language Model Adaptation via Representer Theorem

Kun Ding, Ying Wang, Gaofeng Meng +1

The advent of pre-trained vision-language foundation models has revolutionized the field of zero/few-shot (i.e., low-shot) image recognition. The key challenge to address under the…

cs.CV2024

Calibrated Cache Model for Few-Shot Vision-Language Model Adaptation

Kun Ding, Qiang Yu, Haojian Zhang +2

Cache-based approaches stand out as both effective and efficient for adapting vision-language models (VLMs). Nonetheless, the existing cache model overlooks three crucial aspects.…

cs.CV2024★ 1 cited

AddressCLIP: Empowering Vision-Language Models for City-wide Image Address Localization

Shixiong Xu, Chenghao Zhang, Lubin Fan +3

In this study, we introduce a new problem raised by social media and photojournalism, named Image Address Localization (IAL), which aims to predict the readable textual address whe…

cs.CV2022★ 2 cited

Pro-tuning: Unified Prompt Tuning for Vision Tasks

Xing Nie, Bolin Ni, Jianlong Chang +6

In computer vision, fine-tuning is the de-facto approach to leverage pre-trained vision models to perform downstream tasks. However, deploying it in practice is quite challenging,…