model pruning

Pruning Multilingual Large Language Models for Multilingual Inference EMNLP 2024 Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices NeurIPS 2024 Resource-Efficient Transformer Pruning for Finetuning of Large Models CVPR 2024 Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization EMNLP 2024 SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead NeurIPS 2024 SparseLLM: Towards Global Pruning of Pre-trained Language Models NeurIPS 2024 Speech Boosting: Low-Latency Live Speech Enhancement for TWS Earbuds Interspeech 2024 Streamlining Speech Enhancement DNNs: an Automated Pruning Method Based on Dependency Graph with Advanced Regularized Loss Strategies Interspeech 2024 Synergistic Patch Pruning for Vision Transformer: Unifying Intra- & Inter-Layer Patch Importance ICLR 2024 The LLM Surgeon ICLR 2024 The Open-World Lottery Ticket Hypothesis for OOD Intent Classification COLING 2024 Towards Meta-Pruning via Optimal Transport ICLR 2024 Unraveling Babel: Exploring Multilingual Activation Patterns of LLMs and Their Applications EMNLP 2024 When Compression Meets Model Compression: Memory-Efficient Double Compression for Large Language Models EMNLP 2024 xCOMET-lite: Bridging the Gap Between Efficiency and Quality in Learned MT Evaluation Metrics EMNLP 2024 Bias in Pruned Vision Models: In-Depth Analysis and Countermeasures CVPR 2023 Breaking through Deterministic Barriers: Randomized Pruning Mask Generation and Selection EMNLP 2023 Break It Down: Evidence for Structural Compositionality in Neural Networks NeurIPS 2023 Can We Find Strong Lottery Tickets in Generative Models? AAAI 2023 COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models ICML 2023 Complement Sparsification: Low-Overhead Model Pruning for Federated Learning AAAI 2023 Data Pruning for Efficient Model Pruning in Neural Machine Translation EMNLP 2023 Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness AAAI 2023 DepthFL : Depthwise Federated Learning for Heterogeneous Clients ICLR 2023 Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers NeurIPS 2023