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Model Compression

124 directly classified papers

Papers per year

Papers

The Mamba in the Llama: Distilling and Accelerating Hybrid Models NIPS 2024
Binarized Spectral Compressive Imaging NIPS 2023
TinyNeRF: Towards 100 x Compression of Voxel Radiance Fields AAAI 2023
Boosting Graph Neural Networks via Adaptive Knowledge Distillation AAAI 2023
Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework AAAI 2023
An Empirical Analysis of Parameter-Efficient Methods for Debiasing Pre-Trained Language Models ACL 2023
A Comparative Study on the Impact of Model Compression Techniques on Fairness in Language Models ACL 2023
YANMTT: Yet Another Neural Machine Translation Toolkit ACL 2023
Unlearning Bias in Language Models by Partitioning Gradients ACL 2023
Efficient On-Device Training via Gradient Filtering CVPR 2023
Re-GAN: Data-Efficient GANs Training via Architectural Reconfiguration CVPR 2023
Adaptive Data-Free Quantization CVPR 2023
Joint Token Pruning and Squeezing Towards More Aggressive Compression of Vision Transformers CVPR 2023
Discriminator-Cooperated Feature Map Distillation for GAN Compression CVPR 2023
DistilPose: Tokenized Pose Regression With Heatmap Distillation CVPR 2023
Enhancing Abstractiveness of Summarization Models through Calibrated Distillation EMNLP 2023
One-Step Diffusion Distillation via Deep Equilibrium Models NIPS 2023
From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression AAAI 2022
Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions NIPS 2022
Fairness Reprogramming NIPS 2022
Knowledge Distillation: Bad Models Can Be Good Role Models NIPS 2022
Deep Model Reassembly NIPS 2022
To update or not to update? Neurons at equilibrium in deep models NIPS 2022
A Win-win Deal: Towards Sparse and Robust Pre-trained Language Models NIPS 2022
BiMLP: Compact Binary Architectures for Vision Multi-Layer Perceptrons NIPS 2022