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Model Compression

1503 directly classified papers

Papers per year

Papers

Enhancing In-Context Learning Performance with just SVD-Based Weight Pruning: A Theoretical Perspective NIPS 2024
Learning Cut Generating Functions for Integer Programming NIPS 2024
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models NIPS 2024
Sparse maximal update parameterization: A holistic approach to sparse training dynamics NIPS 2024
S-STE: Continuous Pruning Function for Efficient 2:4 Sparse Pre-training NIPS 2024
Adaptive Depth Networks with Skippable Sub-Paths NIPS 2024
MediSwift: Efficient Sparse Pre-trained Biomedical Language Models ACL 2024
The Mamba in the Llama: Distilling and Accelerating Hybrid Models NIPS 2024
Linearly Decomposing and Recomposing Vision Transformers for Diverse-Scale Models NIPS 2024
Stylus: Automatic Adapter Selection for Diffusion Models NIPS 2024
DoRA: Enhancing Parameter-Efficient Fine-Tuning with Dynamic Rank Distribution ACL 2024
Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models NIPS 2024
Binarized Diffusion Model for Image Super-Resolution NIPS 2024
Value-Based Deep Multi-Agent Reinforcement Learning with Dynamic Sparse Training NIPS 2024
Integer Is Enough: When Vertical Federated Learning Meets Rounding AAAI 2024
PTMQ: Post-training Multi-Bit Quantization of Neural Networks AAAI 2024
Distilling Autoregressive Models to Obtain High-Performance Non-autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed AAAI 2024
Progressively Knowledge Distillation via Re-parameterizing Diffusion Reverse Process AAAI 2024
Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning AAAI 2024
Cluster-Learngene: Inheriting Adaptive Clusters for Vision Transformers NIPS 2024
ConsistentEE: A Consistent and Hardness-Guided Early Exiting Method for Accelerating Language Models Inference AAAI 2024
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood NIPS 2024
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization NIPS 2024
CQIL: Inference Latency Optimization with Concurrent Computation of Quasi-Independent Layers ACL 2024
Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models NIPS 2024