Ruixuan Li

Full Professor@Huazhong University of Science and Technology·中国·OpenReview

研究方向

natural language processing · named entity recognition · event extraction · text mining · clustering and classification · recommendation · prediction · style transfer · machine learning · deep learning · graph neural networks · distributed machine learning · few-shot learning · explainable artificial intelligence · big data processing and analysis · distributed · cloud and edge computing · data security · privacy protection · AI security · generative adversarial network

Ruixuan Li

BoRA: Towards More Expressive Low-Rank Adaptation with Block Diversity

Breaking Static Paradigms: A Mutual Evolution Framework for Edge-Cloud Model Collaboration

FastEdit: Low-Rank Structured Regularization for Efficient Model Editing

ContrastGen: A Multi-agent Contrastive Framework for Hard Retrieval Data Generation

Enhancing RAG with Active Learning on Conversation Records: Reject Incapables and Answer Capables

You Don't Have to Be the One Doing Evil! Locate a Scapegoat within Multi-Agent Systems for Executing Covert Attacks

Model Editing is Over: Revealing Its Illusory Success and Fragile Foundation

SAFD: A Style-Agnostic Framework for Detecting LLM-Generated Text

C$^2$-AFCL: Cross-task Calibration for Asynchronous Federated Continual Learning

FedSSI: Rehearsal-Free Continual Federated Learning with Synergistic Synaptic Intelligence

Efficient Knowledge Transfer in Federated Recommendation for Joint Venture Ecosystem

Beyond Higher Rank: Token-wise Input-Output Projections for Efficient Low-Rank Adaptation

BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach

ChatbotID: Identifying Chatbots with Granger Causality Test

Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization

FlowCut: Rethinking Redundancy via Information Flow for Efficient Vision-Language Models

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation

Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation

Beyond Zero Initialization: Investigating the Impact of Non-Zero Initialization on LoRA Fine-Tuning Dynamics

Resource-Constrained Federated Continual Learning: What Does Matter?

Feature Distillation is the Better Choice for Model-Heterogeneous Federated Learning

Enhancing Privacy in Multimodal Federated Learning with Information Theory

Random Registers for Cross-Domain Few-Shot Learning

Revisiting Continuity of Image Tokens for Cross-domain Few-shot Learning

Rehearsal-Free Continual Federated Learning with Synergistic Regularization

Breaking Free from MMI: A New Frontier in Rationalization by Probing Input Utilization

Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets

The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning

A Decoupled Learning Framework for Neural Marked Temporal Point Process

Attacking for Inspection and Instruction: Attack Techniques Can Aid In Interpretability