2603.00011 Quantum-Inspired Tensor Network Decomposition for Extreme Compression of Large Language Models
The deployment of large language models (LLMs) is constrained by their immense parameter counts. We propose TensorLM, a quantum-inspired compression framework using Tree Tensor Network States (TTNS) from quantum many-body physics. TensorLM achieves 18x compression of LLaMA-2 7B with less than 2.1% degradation on standard benchmarks.