QuanT A: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation

We propose Quan tum-informed T ensor A daptation ( QuanT A), a novel, easy-to-implement, fine-tuning method with no inference overhead for large-scale pre-trained language models.