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20202026
most citedQuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation

6 citations · 10 across the 7 of their papers we have counts for

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Showing 2024Show all

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cs.CL2024

OccamLLM: Fast and Exact Language Model Arithmetic in a Single Step

Owen Dugan, Donato Manuel Jimenez Beneto, Charlotte Loh +3

Despite significant advancements in text generation and reasoning, Large Language Models (LLMs) still face challenges in accurately performing complex arithmetic operations. Langua…

cs.LG2024★ 6 cited

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

Zhuo Chen, Rumen Dangovski, Charlotte Loh +3

We propose Quantum-informed Tensor Adaptation (QuanTA), a novel, easy-to-implement, fine-tuning method with no inference overhead for large-scale pre-trained language models. By le…