1 citations · 2 across the 4 of their papers we have counts for
4 papers
Aligning LLM Uncertainty with Human Disagreement in Subjectivity Analysis
Junyu Lu, Deyi Ji, Xuanyi Liu +5
Large language models for subjectivity analysis are typically trained with aggregated labels, which compress variations in human judgment into a single supervision signal. This par…
Anti-Collapse Loss for Deep Metric Learning Based on Coding Rate Metric
Xiruo Jiang, Yazhou Yao, Xili Dai +3
Deep metric learning (DML) aims to learn a discriminative high-dimensional embedding space for downstream tasks like classification, clustering, and retrieval. Prior literature pre…
Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection
Huafeng Liu, Mengmeng Sheng, Zeren Sun +3
Learning with noisy labels has gained increasing attention because the inevitable imperfect labels in real-world scenarios can substantially hurt the deep model performance. Recent…
Hierarchical Graph Pattern Understanding for Zero-Shot VOS
Gensheng Pei, Fumin Shen, Yazhou Yao +3
The optical flow guidance strategy is ideal for obtaining motion information of objects in the video. It is widely utilized in video segmentation tasks. However, existing optical f…