Is the Number of Trainable Parameters All That Actually Matters?

24 September 2021

Papers citing "Is the Number of Trainable Parameters All That Actually Matters?"

5 / 5 papers shown

Title
A Moonshot for AI Oracles in the Sciences Bryan Kaiser Tailin Wu Maike Sonnewald Colin Thackray Skylar Callis AI4CE 51 0 0 25 Jun 2024
A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Software Engineering Tasks Wentao Zou Qi Li Jidong Ge Chuanyi Li Xiaoyu Shen LiGuo Huang Bin Luo 24 5 0 25 Dec 2023
Scaling Laws Beyond Backpropagation Matthew J. Filipovich Alessandro Cappelli Daniel Hesslow Julien Launay 19 3 0 26 Oct 2022
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers Boseop Kim Hyoungseok Kim Sang-Woo Lee Gichang Lee Donghyun Kwak ... Jaewook Kang Inho Kang Jung-Woo Ha W. Park Nako Sung VLM 243 121 0 10 Sep 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 228 4,460 0 23 Jan 2020