Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with
Accelerated LLMs

Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs

2 August 2024

Boian Alexandrov

Manish Bhattarai

Papers citing "Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs"

5 / 5 papers shown

Title
TT-LoRA MoE: Unifying Parameter-Efficient Fine-Tuning and Sparse Mixture-of-Experts Pradip Kunwar Minh Vu Maanak Gupta Mahmoud Abdelsalam Manish Bhattarai MoE MoMe 187 0 0 29 Apr 2025
Tensor Networks Meet Neural Networks: A Survey and Future Perspectives Maolin Wang Yu Pan Zenglin Xu Xiangli Yang Guangxi Li A. Cichocki Andrzej Cichocki 58 19 0 22 Jan 2023
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 238 808 0 14 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,872 0 18 Apr 2021
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 299 6,984 0 20 Apr 2018