Gen Li

Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models

Forget-It-All: Multi-Concept Machine Unlearning via Concept-Aware Neuron Masking

From Bits to Chips: An LLM-based Hardware-Aware Quantization Agent for Streamlined Deployment of LLMs

LightCache: Memory-Efficient, Training-Free Acceleration for Video Generation

The Right to be Forgotten in Pruning: Unveil Machine Unlearning on Sparse Models

A Single-Step, Sharpness-Aware Minimization is All You Need to Achieve Efficient and Accurate Sparse Training

NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization

Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-Design

BiDST: Dynamic Sparse Training is a Bi-Level Optimization Problem

Coupling Fairness and Pruning in a Single Run: a Bi-level Optimization Perspective