Ruijiang Dong — accepted AI-conference papers

2026

CARPRT: Class-Aware Zero-Shot Prompt Reweighting for Vision-Language Model

Ruijiang Dong, Zesheng Ye, Feng Liu, Jianzhong Qi, Lei Feng, Gang Niu +1

ICLR 2026poster

Pre-trained vision-language models (VLMs) enable zero-shot image classification by computing the similarity score between an image and textual descriptions, typically formed by inserting a class label (e.g., "cat") into a prompt (e.g., "a photo of a").Existing studies have shown that the score betwe…

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2023

Diversity-enhancing Generative Network for Few-shot Hypothesis Adaptation

Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu +2

ICML 2023poster

Generating unlabeled data has been recently shown to help address the few-shot hypothesis adaptation (FHA) problem, where we aim to train a classifier for the target domain with a few labeled target-domain data and a well-trained source-domain classifier (i.e., a source hypothesis), for the addition…

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