How Well Can Transformers Emulate In-context Newton's Method?

5 March 2024

Papers citing "How Well Can Transformers Emulate In-context Newton's Method?"

6 / 6 papers shown

Title
Vector-ICL: In-context Learning with Continuous Vector Representations Yufan Zhuang Chandan Singh Liyuan Liu Jingbo Shang Jianfeng Gao 52 3 0 21 Feb 2025
Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent Bo Chen Xiaoyu Li Yingyu Liang Zhenmei Shi Zhao-quan Song 83 19 0 15 Oct 2024
On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding Kevin Xu Issei Sato 37 3 0 02 Oct 2024
Transformers Handle Endogeneity in In-Context Linear Regression Haodong Liang Krishnakumar Balasubramanian Lifeng Lai 36 1 0 02 Oct 2024
Looped Transformers are Better at Learning Learning Algorithms Liu Yang Kangwook Lee Robert D. Nowak Dimitris Papailiopoulos 24 24 0 21 Nov 2023
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 315 8,448 0 28 Jan 2022