Model Compression

Multi-Level Logit Distillation CVPR 2023 MUter: Machine Unlearning on Adversarially Trained Models ICCV 2023 MUX-PLMs: Pre-training Language Models with Data Multiplexing ACL 2023 NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models EMNLP 2023 NeRN: Learning Neural Representations for Neural Networks ICLR 2023 Neural Polarizer: A Lightweight and Effective Backdoor Defense via Purifying Poisoned Features NeurIPS 2023 NIPQ: Noise Proxy-Based Integrated Pseudo-Quantization CVPR 2023 NNSplitter: An Active Defense Solution for DNN Model via Automated Weight Obfuscation ICML 2023 NORM: Knowledge Distillation via N-to-One Representation Matching ICLR 2023 OMPQ: Orthogonal Mixed Precision Quantization AAAI 2023 One-bit Flip is All You Need: When Bit-flip Attack Meets Model Training ICCV 2023 One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning NeurIPS 2023 One Network, Many Masks: Towards More Parameter-Efficient Transfer Learning ACL 2023 On Enhancing Fine-Tuning for Pre-trained Language Models EMNLP 2023 One-Shot Model for Mixed-Precision Quantization CVPR 2023 One Wide Feedforward Is All You Need EMNLP 2023 On Prefix-tuning for Lightweight Out-of-distribution Detection ACL 2023 On Quantizing Implicit Neural Representations WACV 2023 On the Effectiveness of Parameter-Efficient Fine-Tuning AAAI 2023 OpenDelta: A Plug-and-play Library for Parameter-efficient Adaptation of Pre-trained Models ACL 2023 Optimizing Retrieval-augmented Reader Models via Token Elimination EMNLP 2023 OPTQ: Accurate Quantization for Generative Pre-trained Transformers ICLR 2023 ORC: Network Group-based Knowledge Distillation using Online Role Change ICCV 2023 OTOv2: Automatic, Generic, User-Friendly ICLR 2023 Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling EMNLP 2023