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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.LG2026

Variational Inference for Evidential Deep Learning

Jiawei Tang, Xinyan Du, Hui Liu +2

The paper introduces VI-EDL, a variational inference framework for evidential deep learning that controls evidence growth and provides theoretical guarantees for uncertainty estima…

cs.LG2026

Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-Supervised Learning

Yaxin Hou, Jun Ma, Hanyang Li +3

Semi-supervised learning faces significant challenges in realistic scenarios where labeled data is scarce and unlabeled data follows unknown, arbitrary distributions. We formalize…

cs.LG2026

Language-Assisted Image Clustering Guided by Discriminative Relational Signals and Adaptive Semantic Centers

Jun Ma, Xu Zhang, Zhengxing Jiao +4

Language-Assisted Image Clustering (LAIC) augments the input images with additional texts with the help of vision-language models (VLMs) to promote clustering performance. Despite…

cs.CV2026

Attribute Distribution Modeling and Semantic-Visual Alignment for Generative Zero-shot Learning

Haojie Pu, Zhuoming Li, Yongbiao Gao +1

Generative zero-shot learning (ZSL) synthesizes features for unseen classes, leveraging semantic conditions to transfer knowledge from seen classes. However, it also introduces two…

cs.LG2025

Partial Label Clustering

Yutong Xie, Fuchao Yang, Yuheng Jia

Partial label learning (PLL) is a significant weakly supervised learning framework, where each training example corresponds to a set of candidate labels and only one label is the g…