9 citations · 33 across the 18 of their papers we have counts for
6 papers · 1 filter
Self-Ensembling Vision-Language Models for Chart Data Extraction
Thomas Berkane, Qianyi Wang, Maimuna S. Majumder
Charts effectively convey quantitative information, but the underlying data are often locked in image form, hindering reuse and analysis. Manually digitizing charts is time-consumi…
Transfer and Alignment Network for Generalized Category Discovery
Wenbin An, Feng Tian, Wenkai Shi +4
Generalized Category Discovery is a crucial real-world task. Despite the improved performance on known categories, current methods perform poorly on novel categories. We attribute…
Generalized Category Discovery with Large Language Models in the Loop
Wenbin An, Wenkai Shi, Feng Tian +8
Generalized Category Discovery (GCD) is a crucial task that aims to recognize both known and novel categories from a set of unlabeled data by utilizing a few labeled data with only…
A Diffusion Weighted Graph Framework for New Intent Discovery
Wenkai Shi, Wenbin An, Feng Tian +3
New Intent Discovery (NID) aims to recognize both new and known intents from unlabeled data with the aid of limited labeled data containing only known intents. Without considering…
Generalized Category Discovery with Decoupled Prototypical Network
Wenbin An, Feng Tian, Qinghua Zheng +3
Generalized Category Discovery (GCD) aims to recognize both known and novel categories from a set of unlabeled data, based on another dataset labeled with only known categories. Wi…
Fine-grained Category Discovery under Coarse-grained supervision with Hierarchical Weighted Self-contrastive Learning
Wenbin An, Feng Tian, Ping Chen +3
Novel category discovery aims at adapting models trained on known categories to novel categories. Previous works only focus on the scenario where known and novel categories are of…