Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs

28 April 2023

Papers citing "Empirical Analysis of the Strengths and Weaknesses of PEFT Techniques for LLMs"

6 / 6 papers shown

Title
GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning Hasna Chouikhi Manel Aloui Cyrine Ben Hammou Ghaith Chaabane Haithem Kchaou Chehir Dhaouadi 44 0 0 02 Jul 2024
ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts Samar Khanna Medhanie Irgau David B. Lobell Stefano Ermon VLM 32 4 0 16 Jun 2024
Mixed Text Recognition with Efficient Parameter Fine-Tuning and Transformer Da Chang Yu Li 72 2 0 19 Apr 2024
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes Zhen Qin Daoyuan Chen Bingchen Qian Bolin Ding Yaliang Li Shuiguang Deng FedML 45 32 0 11 Dec 2023
Multitask Prompted Training Enables Zero-Shot Task Generalization Victor Sanh Albert Webson Colin Raffel Stephen H. Bach Lintang Sutawika ... T. Bers Stella Biderman Leo Gao Thomas Wolf Alexander M. Rush LRM 218 1,663 0 15 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