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model compression

3283 papers

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MC

Co-occurring keywords

knowledge distillation (3680) large language model (12755) neural network (6616) efficient computing (779) neural network optimization (1293) transfer learning (5442) convolutional neural network (4216) neural network pruning (265) language model (4573) parameter efficiency (415)

Papers

Compact Speech Translation Models via Discrete Speech Units Pretraining ACL 2024
IT-Tuning : Parameter Efficient Information Token Tuning for Language Model ACL 2024
SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead NIPS 2024
Transforming Vision Transformer: Towards Efficient Multi-Task Asynchronous Learner NIPS 2024
Progressively Knowledge Distillation via Re-parameterizing Diffusion Reverse Process AAAI 2024
UPS: Unified Projection Sharing for Lightweight Single-Image Super-resolution and Beyond NIPS 2024
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework NIPS 2024
Efficient Large Multi-modal Models via Visual Context Compression NIPS 2024
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation NIPS 2024
Expanding Sparse Tuning for Low Memory Usage NIPS 2024
Cross-model Control: Improving Multiple Large Language Models in One-time Training NIPS 2024
Context-Aware Assistant Selection for Improved Inference Acceleration with Large Language Models EMNLP 2024
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models EMNLP 2024
Group and Shuffle: Efficient Structured Orthogonal Parametrization NIPS 2024
Toward Efficient Inference for Mixture of Experts NIPS 2024
Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization EMNLP 2024
MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning EMNLP 2024
PTQ4DiT: Post-training Quantization for Diffusion Transformers NIPS 2024
QUIK: Towards End-to-end 4-Bit Inference on Generative Large Language Models EMNLP 2024
BMRS: Bayesian Model Reduction for Structured Pruning NIPS 2024
BOLD: Boolean Logic Deep Learning NIPS 2024
From Bottom to Top: Extending the Potential of Parameter Efficient Fine-Tuning EMNLP 2024
Federated Model Heterogeneous Matryoshka Representation Learning NIPS 2024
BAM! Just Like That: Simple and Efficient Parameter Upcycling for Mixture of Experts NIPS 2024
DeltaDEQ: Exploiting Heterogeneous Convergence for Accelerating Deep Equilibrium Iterations NIPS 2024