Model Compression

EMO: Embedding Model Distillation via Intra-Model Relation and Optimal Transport Alignments EMNLP 2025 Enabling Visual Foundation Models to Teach Compact Students via Mixture of Distillation IJCAI 2025 Enhancing AI-Driven Farming Advisory in Kenya with Efficient RAG Agents via Quantized Fine-Tuned Language Models ACL 2025 Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models RSS 2025 Enhancing Cross-Tokenizer Knowledge Distillation with Contextual Dynamical Mapping ACL 2025 Enhancing Large Language Model Performance with Gradient-Based Parameter Selection AAAI 2025 Enhancing Model Privacy in Federated Learning with Random Masking and Quantization EMNLP 2025 EWoRA: Expert Weighted Low-Rank Adaptation for Heterogeneous Data IJCNLP 2025 Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting ICLR 2025 Exploring Query Efficient Data Generation Towards Data-Free Model Stealing in Hard Label Setting AAAI 2025 Extending Temperature Scaling with Homogenizing Maps JMLR 2025 Extracting General-use Transformers for Low-resource Languages via Knowledge Distillation COLING 2025 Extracting Interpretable Task-Specific Circuits from Large Language Models for Faster Inference AAAI 2025 Fast and Interpretable Mixed-Integer Linear Program Solving by Learning Model Reduction AAAI 2025 Fast and Slow Gradient Approximation for Binary Neural Network Optimization AAAI 2025 Faster Speculative Decoding via Effective Draft Decoder with Pruned Candidate Tree ACL 2025 FaST: Feature-aware Sampling and Tuning for Personalized Preference Alignment with Limited Data EMNLP 2025 Feather the Throttle: Revisiting Visual Token Pruning for Vision-Language Model Acceleration ICCV 2025 Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark ICCV 2025 Federated Graph Condensation with Information Bottleneck Principles AAAI 2025 FedWSQ: Efficient Federated Learning with Weight Standardization and Distribution-Aware Non-Uniform Quantization ICCV 2025 FIMA-Q: Post-Training Quantization for Vision Transformers by Fisher Information Matrix Approximation CVPR 2025 Findings of the WMT 2025 Shared Task on Model Compression: Early Insights on Compressing LLMs for Machine Translation EMNLP 2025 FISTAPruner: Layer-wise Post-training Pruning for Large Language Models EMNLP 2025 FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing NAACL 2025