9 papers
MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification
Da Zhang, Bingyu Li, Zhiyuan Zhao +3
Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existing methods struggle to jointl…
Safeguarding Text-to-Image Generative Models Against Unauthorized Knowledge Distillation
Yilan Gao, Sida Huang, Hongyuan Zhang +1
Closed-weight generative services are increasingly deployed through query-based APIs, where users can obtain generated outputs while model parameters remain inaccessible. However,…
Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise
Hongyuan Zhang, Yanchen Xu, Sida Huang +1
Inspired by the idea of Positive-incentive Noise (Pi-Noise or -Noise) that aims at learning the reliable noise beneficial to tasks, we scientifically investigate the connection…
GRPO-RM: Fine-Tuning Representation Models via GRPO-Driven Reinforcement Learning
Yanchen Xu, Ziheng Jiao, Hongyuan Zhang +1
The Group Relative Policy Optimization (GRPO), a reinforcement learning method used to fine-tune large language models (LLMs), has proved its effectiveness in practical application…
Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning
Kai Jiang, Zhengyan Shi, Dell Zhang +2
Class Incremental Learning (CIL) aims to continuously learn new categories while retaining the knowledge of old ones. Pre-trained models (PTMs) show promising capabilities in CIL.…
Variational Positive-incentive Noise: How Noise Benefits Models
Hongyuan Zhang, Sida Huang, Yubin Guo +1
A large number of works aim to alleviate the impact of noise due to an underlying conventional assumption of the negative role of noise. However, some existing works show that the…