3 citations · 8 across the 8 of their papers we have counts for
8 papers
Contextuality Helps Representation Learning for Generalized Category Discovery
Tingzhang Luo, Mingxuan Du, Jiatao Shi +3
This paper introduces a novel approach to Generalized Category Discovery (GCD) by leveraging the concept of contextuality to enhance the identification and classification of catego…
Labeled Data Selection for Category Discovery
Bingchen Zhao, Nico Lang, Serge Belongie +1
Category discovery methods aim to find novel categories in unlabeled visual data. At training time, a set of labeled and unlabeled images are provided, where the labels correspond…
Benchmarking Multi-Image Understanding in Vision and Language Models: Perception, Knowledge, Reasoning, and Multi-Hop Reasoning
Bingchen Zhao, Yongshuo Zong, Letian Zhang +1
The advancement of large language models (LLMs) has significantly broadened the scope of applications in natural language processing, with multi-modal LLMs extending these capabili…
What If We Recaption Billions of Web Images with LLaMA-3?
Xianhang Li, Haoqin Tu, Mude Hui +9
Web-crawled image-text pairs are inherently noisy. Prior studies demonstrate that semantically aligning and enriching textual descriptions of these pairs can significantly enhance…
Beyond Known Clusters: Probe New Prototypes for Efficient Generalized Class Discovery
Ye Wang, Yaxiong Wang, Yujiao Wu +2
Generalized Class Discovery (GCD) aims to dynamically assign labels to unlabelled data partially based on knowledge learned from labelled data, where the unlabelled data may come f…
HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing
Mude Hui, Siwei Yang, Bingchen Zhao +5
This study introduces HQ-Edit, a high-quality instruction-based image editing dataset with around 200,000 edits. Unlike prior approaches relying on attribute guidance or human feed…