Learning Functional Subspaces for Neural Network Compression
cs.LG, cs.CL
Submitted: 2026-09-30
Updated: 2026-09-30
Code: https://github.com/tatsu-lab/stanford_alpaca
Terminology
Sources
- Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
- DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
- Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
- Distilling the Knowledge in a Neural Network
- Low-rank bias, weight decay, and model merging in neural networks
- ProxSparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs
- Understanding Calibration and Truncation Error Propagation in Training-Free Low-Rank Compression for LLMs
- WinoGrande: An Adversarial Winograd Schema Challenge at Scale
- Llama 2: Open Foundation and Fine-Tuned Chat Models
- Qwen3 Technical Report
- ASVD: Activation-aware Singular Value Decomposition for Compressing Large Language Models
- OPT: Open Pre-trained Transformer Language Models
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