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Model Compression

1928 directly classified papers

Papers per year

Papers

STEP: Learning N:M Structured Sparsity Masks from Scratch with Precondition ICML 2023

Gradient-Free Structured Pruning with Unlabeled Data ICML 2023

Understanding Int4 Quantization for Language Models: Latency Speedup, Composability, and Failure Cases ICML 2023

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models ICML 2023

SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference ICML 2023

Bi-directional Masks for Efficient N:M Sparse Training ICML 2023

Shapley Head Pruning: Identifying and Removing Interference in Multilingual Transformers EACL 2023

Finding the Pillars of Strength for Multi-Head Attention ACL 2023

Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks ACL 2023

Exploring the Relative Value of Collaborative Optimisation Pathways (Student Abstract) AAAI 2023

Small Pre-trained Language Models Can be Fine-tuned as Large Models via Over-Parameterization ACL 2023

Gradient-based Intra-attention Pruning on Pre-trained Language Models ACL 2023

Rethinking Data-Free Quantization as a Zero-Sum Game AAAI 2023

Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features NIPS 2023

Improving Adversarial Robustness via Information Bottleneck Distillation NIPS 2023

Towards Efficient and Accurate Winograd Convolution via Full Quantization NIPS 2023

Your representations are in the network: composable and parallel adaptation for large scale models NIPS 2023

Rethinking Conditional Diffusion Sampling with Progressive Guidance NIPS 2023

SUBP: Soft Uniform Block Pruning for 1$\times$N Sparse CNNs Multithreading Acceleration NIPS 2023

Probabilistic Weight Fixing: Large-scale training of neural network weight uncertainties for quantisation. NIPS 2023

Pruning vs Quantization: Which is Better? NIPS 2023

Don’t just prune by magnitude! Your mask topology is a secret weapon NIPS 2023

Dynamic Sparsity Is Channel-Level Sparsity Learner NIPS 2023

Teacher Intervention: Improving Convergence of Quantization Aware Training for Ultra-Low Precision Transformers EACL 2023

TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration NIPS 2023