Model Compression

SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors NeurIPS 2024 SwapMoE: Serving Off-the-shelf MoE-based Large Language Models with Tunable Memory Budget ACL 2024 SwitchHead: Accelerating Transformers with Mixture-of-Experts Attention NeurIPS 2024 Taylor Unswift: Secured Weight Release for Large Language Models via Taylor Expansion EMNLP 2024 Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization AAAI 2024 TFMQ-DM: Temporal Feature Maintenance Quantization for Diffusion Models CVPR 2024 The Mamba in the Llama: Distilling and Accelerating Hybrid Models NeurIPS 2024 Time is Encoded in the Weights of Finetuned Language Models ACL 2024 Token Fusion: Bridging the Gap Between Token Pruning and Token Merging WACV 2024 Torque Based Structured Pruning for Deep Neural Network WACV 2024 Toward Efficient Inference for Mixture of Experts NeurIPS 2024 Towards Better Structured Pruning Saliency by Reorganizing Convolution WACV 2024 Towards Efficient Verification of Quantized Neural Networks AAAI 2024 Towards Efficient Visual-Language Alignment of the Q-Former for Visual Reasoning Tasks EMNLP 2024 Towards More Accurate Diffusion Model Acceleration with A Timestep Tuner CVPR 2024 Towards Next-Level Post-Training Quantization of Hyper-Scale Transformers NeurIPS 2024 Training Binary Neural Networks via Gaussian Variational Inference and Low-Rank Semidefinite Programming NeurIPS 2024 Turn Waste into Worth: Rectifying Top-k Router of MoE EMNLP 2024 Twin-Merging: Dynamic Integration of Modular Expertise in Model Merging NeurIPS 2024 UltraSparseBERT: 99% Conditionally Sparse Language Modelling ACL 2024 Understanding and Minimising Outlier Features in Transformer Training NeurIPS 2024 Understanding the Role of the Projector in Knowledge Distillation AAAI 2024 Ungeneralizable Examples CVPR 2024 Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement NeurIPS 2024 UniPTS: A Unified Framework for Proficient Post-Training Sparsity CVPR 2024