Linear Self-Attention Approximation via Trainable Feedforward Kernel
Paper • 2211.04076 • Published • 1
Approximation
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Greenformer: Factorization Toolkit for Efficient Deep Neural Networks
Paper • 2109.06762 • Published • 1 -
COMCAT: Towards Efficient Compression and Customization of Attention-Based Vision Models
Paper • 2305.17235 • Published • 2 -
Exploring Low Rank Training of Deep Neural Networks
Paper • 2209.13569 • Published • 1 -
Fourier Transformer: Fast Long Range Modeling by Removing Sequence Redundancy with FFT Operator
Paper • 2305.15099 • Published • 1 -
AxFormer: Accuracy-driven Approximation of Transformers for Faster, Smaller and more Accurate NLP Models
Paper • 2010.03688 • Published • 1 -
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition
Paper • 2107.11442 • Published • 1 -
L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient and Accurate Deep Learning
Paper • 2210.17357 • Published • 1 -
The LLM Surgeon
Paper • 2312.17244 • Published • 9 -
Rethinking Compression: Reduced Order Modelling of Latent Features in Large Language Models
Paper • 2312.07046 • Published • 15 -
LORD: Low Rank Decomposition Of Monolingual Code LLMs For One-Shot Compression
Paper • 2309.14021 • Published • 1 -
PELA: Learning Parameter-Efficient Models with Low-Rank Approximation
Paper • 2310.10700 • Published • 1 -
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Paper • 2312.13558 • Published • 5 -
NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning
Paper • 2307.08941 • Published • 1 -
Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations
Paper • 2205.13571 • Published • 1 -
Trained Rank Pruning for Efficient Deep Neural Networks
Paper • 1812.02402 • Published • 1 -
TRP: Trained Rank Pruning for Efficient Deep Neural Networks
Paper • 2004.14566 • Published • 1 -
Factorization Vision Transformer: Modeling Long Range Dependency with Local Window Cost
Paper • 2312.08614 • Published • 1 -
Learning Low-Rank Representations for Model Compression
Paper • 2211.11397 • Published • 1 -
Latent Space Factorisation and Manipulation via Matrix Subspace Projection
Paper • 1907.12385 • Published • 1 -
Rethinking Attention with Performers
Paper • 2009.14794 • Published • 1 -
Softmax-free Linear Transformers
Paper • 2207.03341 • Published • 1 -
Generalization Bounds for Magnitude-Based Pruning via Sparse Matrix Sketching
Paper • 2305.18789 • Published • 1 -
Efficient Storage of Fine-Tuned Models via Low-Rank Approximation of Weight Residuals
Paper • 2305.18425 • Published • 1 -
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models
Paper • 2112.00029 • Published • 1 -
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy
Paper • 2310.01334 • Published • 3 -
LoGAH: Predicting 774-Million-Parameter Transformers using Graph HyperNetworks with 1/100 Parameters
Paper • 2405.16287 • Published • 11 -
Effectively Compress KV Heads for LLM
Paper • 2406.07056 • Published • 1 -
SVD-LLM: Truncation-aware Singular Value Decomposition for Large Language Model Compression
Paper • 2403.07378 • Published • 4 -
On the Benefits of Rank in Attention Layers
Paper • 2407.16153 • Published