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model compression

3302 papers

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MC

Co-occurring keywords

knowledge distillation (3725) large language model (13587) neural network (6616) efficient computing (781) neural network optimization (1293) transfer learning (5449) convolutional neural network (4226) neural network pruning (265) language model (4599) parameter efficiency (417)

Papers

FedPFT: Federated Proxy Fine-Tuning of Foundation Models IJCAI 2024
Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention EMNLP 2024
Balancing Speciality and Versatility: a Coarse to Fine Framework for Supervised Fine-tuning Large Language Model ACL 2024
A Survey on Efficient Federated Learning Methods for Foundation Model Training IJCAI 2024
Pruning via Merging: Compressing LLMs via Manifold Alignment Based Layer Merging EMNLP 2024
BabyLM Challenge: Experimenting with Self-Distillation and Reverse-Distillation for Language Model Pre-Training on Constrained Datasets CONLL 2024
Global-Pruner: A Stable and Efficient Pruner for Retraining-Free Pruning of Encoder-Based Language Models CONLL 2024
NACL: A General and Effective KV Cache Eviction Framework for LLM at Inference Time ACL 2024
Further Compressing Distilled Language Models via Frequency-aware Partial Sparse Coding of Embeddings CONLL 2024
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillation NIPS 2024
Minimal Distillation Schedule for Extreme Language Model Compression EACL 2024
To Distill or Not to Distill? On the Robustness of Robust Knowledge Distillation ACL 2024
Compact 3D Gaussian Representation for Radiance Field CVPR 2024
Learning Low-Rank Tensor Cores with Probabilistic ℓ0-Regularized Rank Selection for Model Compression IJCAI 2024
Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs ACL 2024
Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning EMNLP 2024
DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs NIPS 2024
Unlocking Data-free Low-bit Quantization with Matrix Decomposition for KV Cache Compression ACL 2024
PRoLoRA: Partial Rotation Empowers More Parameter-Efficient LoRA ACL 2024
SpaFL: Communication-Efficient Federated Learning With Sparse Models And Low Computational Overhead NIPS 2024
Rethinking Pruning Large Language Models: Benefits and Pitfalls of Reconstruction Error Minimization EMNLP 2024
QUIK: Towards End-to-end 4-Bit Inference on Generative Large Language Models EMNLP 2024
LRQuant: Learnable and Robust Post-Training Quantization for Large Language Models ACL 2024
MELoRA: Mini-Ensemble Low-Rank Adapters for Parameter-Efficient Fine-Tuning ACL 2024
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework NIPS 2024