ResearchAlpha Leak

Conferences Topics Top Authors Rankings Browse All

Home/Authors/Fei Chao

Fei Chao

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 8:46 PM AMS

22

papers

522

total citations

papers (22)

Towards Compact CNNs via Collaborative Compression

Meta Architecture for Point Cloud Analysis

DiffRate : Differentiable Compression Rate for Efficient Vision Transformers

AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Acceleration

AffineQuant: Affine Transformation Quantization for Large Language Models

Revisiting Discriminator in GAN Compression: A Generator-discriminator Cooperative Compression Scheme

NEURIPS 2021arXiv

Dynamic Dual Trainable Bounds for Ultra-Low Precision Super-Resolution Networks

Fine-Grained Data Distribution Alignment for Post-Training Quantization

SMMix: Self-Motivated Image Mixing for Vision Transformers

Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective

Discriminator-Cooperated Feature Map Distillation for GAN Compression

Learning Image Demoireing from Unpaired Real Data

Determining Layer-wise Sparsity for Large Language Models Through a Theoretical Perspective

Move and Act: Enhanced Object Manipulation and Background Integrity for Image Editing

RepAn: Enhanced Annealing through Re-parameterization

Outlier-aware Slicing for Post-Training Quantization in Vision Transformer

polybasic Speculative Decoding Through a Theoretical Perspective

Learning Best Combination for Efficient N:M Sparsity

Automatic Network Pruning via Hilbert-Schmidt Independence Criterion Lasso under Information Bottleneck Principle

GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models

Neural Architecture Search With Representation Mutual Information

Semantic Alignment and Reinforcement for Data-Free Quantization of Vision Transformers