model compression

Real-Time Image Demoir$\acute{e}$ing on Mobile Devices ICLR 2023 Recasting Self-Attention with Holographic Reduced Representations ICML 2023 Reconstructive Neuron Pruning for Backdoor Defense ICML 2023 Recycle-and-Distill: Universal Compression Strategy for Transformer-based Speech SSL Models with Attention Map Reusing and Masking Distillation Interspeech 2023 Re-GAN: Data-Efficient GANs Training via Architectural Reconfiguration CVPR 2023 Regularized Mask Tuning: Uncovering Hidden Knowledge in Pre-Trained Vision-Language Models ICCV 2023 RepQ-ViT: Scale Reparameterization for Post-Training Quantization of Vision Transformers ICCV 2023 Representation Disparity-aware Distillation for 3D Object Detection ICCV 2023 Resilient Binary Neural Network AAAI 2023 Rethinking Data-Free Quantization as a Zero-Sum Game AAAI 2023 Rethinking Word-Level Auto-Completion in Computer-Aided Translation EMNLP 2023 Retrieval-based Knowledge Transfer: An Effective Approach for Extreme Large Language Model Compression EMNLP 2023 Reusing Pretrained Models by Multi-linear Operators for Efficient Training NeurIPS 2023 Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness NeurIPS 2023 Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference? EMNLP 2023 Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective EACL 2023 Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models EACL 2023 Revisiting the Parameter Efficiency of Adapters from the Perspective of Precision Redundancy ICCV 2023 Revisiting Token Dropping Strategy in Efficient BERT Pretraining ACL 2023 Revisit the Power of Vanilla Knowledge Distillation: from Small Scale to Large Scale NeurIPS 2023 REx: Data-Free Residual Quantization Error Expansion NeurIPS 2023 RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch ICLR 2023 Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding EACL 2023 Rockmate: an Efficient, Fast, Automatic and Generic Tool for Re-materialization in PyTorch ICML 2023 Safety Aware Neural Pruning for Deep Reinforcement Learning (Student Abstract) AAAI 2023