1 citations · 1 across the 4 of their papers we have counts for
5 papers
Vocabulary-Incomplete Unsupervised Vision-Language Model Adaptation
Si Qin, Jiawei Tang, Yaxin Hou +4
In certain real-world scenarios, obtaining labeled data is excessively expensive, motivating increasing interest in adapting models without annotations. Vision-language models (VLM…
Variational Inference for Evidential Deep Learning
Jiawei Tang, Xinyan Du, Hui Liu +2
While Deep Neural Networks (DNNs) achieve remarkable performance, their tendency to produce overconfident predictions. Evidential Deep Learning (EDL) mitigates this by formulating…
Towards Better IncomLDL: We Are Unaware of Hidden Labels in Advance
Jiecheng Jiang, Jiawei Tang, Jiahao Jiang +3
Label distribution learning (LDL) is a novel paradigm that describe the samples by label distribution of a sample. However, acquiring LDL dataset is costly and time-consuming, whic…
Concentration Distribution Learning from Label Distributions
Jiawei Tang, Yuheng Jia
Label distribution learning (LDL) is an effective method to predict the relative label description degree (a.k.a. label distribution) of a sample. However, the label distribution i…
Exploiting Multi-Label Correlation in Label Distribution Learning
Zhiqiang Kou jing wang yuheng jia xin geng
Label Distribution Learning (LDL) is a novel machine learning paradigm that assigns label distribution to each instance. Many LDL methods proposed to leverage label correlation in…