model compression

SAMP: A Model Inference Toolkit of Post-Training Quantization for Text Processing via Self-Adaptive Mixed-Precision EMNLP 2023 ScaleFL: Resource-Adaptive Federated Learning With Heterogeneous Clients CVPR 2023 ScaleKD: Distilling Scale-Aware Knowledge in Small Object Detector CVPR 2023 SCConv: Spatial and Channel Reconstruction Convolution for Feature Redundancy CVPR 2023 Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective ICLR 2023 Segmented Recurrent Transformer: An Efficient Sequence-to-Sequence Model EMNLP 2023 Self-Decoupling and Ensemble Distillation for Efficient Segmentation AAAI 2023 Self-Distilled Quantization: Achieving High Compression Rates in Transformer-Based Language Models ACL 2023 SFT-KD-Recon: Learning a Student-friendly Teacher for Knowledge Distillation in Magnetic Resonance Image Reconstruction MIDL 2023 Shapley Head Pruning: Identifying and Removing Interference in Multilingual Transformers EACL 2023 SHARCS: Efficient Transformers Through Routing with Dynamic Width Sub-networks EMNLP 2023 Sharing Encoder Representations across Languages, Domains and Tasks in Large-Scale Spoken Language Understanding ACL 2023 ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer NeurIPS 2023 Shortcut-V2V: Compression Framework for Video-to-Video Translation Based on Temporal Redundancy Reduction ICCV 2023 SKDBERT: Compressing BERT via Stochastic Knowledge Distillation AAAI 2023 SLAMB: Accelerated Large Batch Training with Sparse Communication ICML 2023 Slimmed Asymmetrical Contrastive Learning and Cross Distillation for Lightweight Model Training NeurIPS 2023 Small Pre-trained Language Models Can be Fine-tuned as Large Models via Over-Parameterization ACL 2023 SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models ICML 2023 Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective CVPR 2023 SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference ICCV 2023 SparseGPT: Massive Language Models Can be Accurately Pruned in One-Shot ICML 2023 Sparse Low-rank Adaptation of Pre-trained Language Models EMNLP 2023 SparseMAE: Sparse Training Meets Masked Autoencoders ICCV 2023 Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers ICLR 2023