← Application Areas
Machine Learning › Application Areas ›

Model Compression

1503 directly classified papers

Papers per year

Papers

LVPruning: An Effective yet Simple Language-Guided Vision Token Pruning Approach for Multi-modal Large Language Models NAACL 2025
How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM? NAACL 2025
TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data NAACL 2025
MoLA: MoE LoRA with Layer-wise Expert Allocation NAACL 2025
RankAdaptor: Hierarchical Rank Allocation for Efficient Fine-Tuning Pruned LLMs via Performance Model NAACL 2025
As easy as PIE: understanding when pruning causes language models to disagree NAACL 2025
Optimizing LLMs for Italian: Reducing Token Fertility and Enhancing Efficiency Through Vocabulary Adaptation NAACL 2025
UNLEARN Efficient Removal of Knowledge in Large Language Models NAACL 2025
Aligning Sizes of Intermediate Layers by LoRA Adapter for Knowledge Distillation NAACL 2025
Large Language Models Are Overparameterized Text Encoders NAACL 2025
Variance-Based Pruning for Accelerating and Compressing Trained Networks ICCV 2025
GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMs ACL 2025
Beyond Low-Rank Tuning: Model Prior-Guided Rank Allocation for Effective Transfer in Low-Data and Large-Gap Regimes. ICCV 2025
Dense2MoE: Restructuring Diffusion Transformer to MoE for Efficient Text-to-Image Generation ICCV 2025
Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLM ICCV 2025
MixA-Q: Revisiting Activation Sparsity for Vision Transformers from a Mixed-Precision Quantization Perspective ICCV 2025
LiT: Delving into a Simple Linear Diffusion Transformer for Image Generation ICCV 2025
GenieBlue: Integrating both Linguistic and Multimodal Capabilities for Large Language Models on Mobile Devices ICCV 2025
Saliency-Aware Quantized Imitation Learning for Efficient Robotic Control ICCV 2025
Quaff: Quantized Parameter-Efficient Fine-Tuning under Outlier Spatial Stability Hypothesis ACL 2025
Semantic Alignment and Reinforcement for Data-Free Quantization of Vision Transformers ICCV 2025
Make Your Training Flexible: Towards Deployment-Efficient Video Models ICCV 2025
General Compression Framework for Efficient Transformer Object Tracking ICCV 2025
AHCPTQ: Accurate and Hardware-Compatible Post-Training Quantization for Segment Anything Model ICCV 2025
EA-Vit: Efficient Adaptation for Elastic Vision Transformer ICCV 2025