most citedRobust Learning under Hybrid Noise

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation

Maolin Wang, Tianshuo Wei, Sheng Zhang +6

Neural Architecture Search (NAS) has emerged as a powerful approach for automating neural network design. However, existing NAS methods face critical limitations in real-world depl…

cs.IR2025

FindRec: Stein-Guided Entropic Flow for Multi-Modal Sequential Recommendation

Maolin Wang, Yutian Xiao, Binhao Wang +6

Modern recommendation systems face significant challenges in processing multimodal sequential data, particularly in temporal dynamics modeling and information flow coordination. Tr…

cs.CV2025

MiraGe: Multimodal Discriminative Representation Learning for Generalizable AI-Generated Image Detection

Kuo Shi, Jie Lu, Shanshan Ye +2

Recent advances in generative models have highlighted the need for robust detectors capable of distinguishing real images from AI-generated images. While existing methods perform w…

cs.CL2025

Training-free LLM Merging for Multi-task Learning

Zichuan Fu, Xian Wu, Yejing Wang +6

Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse natural language processing (NLP) tasks. The release of open-source LLMs like LLaMA and Qwen…

cs.LG20241 cited

Robust Learning under Hybrid Noise

Yang Wei, Shuo Chen, Shanshan Ye +2

Feature noise and label noise are ubiquitous in practical scenarios, which pose great challenges for training a robust machine learning model. Most previous approaches usually deal…