What can a Single Attention Layer Learn? A Study Through the Random Features Lens

21 July 2023

Papers citing "What can a Single Attention Layer Learn? A Study Through the Random Features Lens"

8 / 8 papers shown

Title
HSR-Enhanced Sparse Attention Acceleration Bo Chen Yingyu Liang Zhizhou Sha Zhenmei Shi Zhao-quan Song 84 18 0 14 Oct 2024
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers Lorenzo Tiberi Francesca Mignacco Kazuki Irie H. Sompolinsky 42 6 0 24 May 2024
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining Licong Lin Yu Bai Song Mei OffRL 30 42 0 12 Oct 2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4 Sébastien Bubeck Varun Chandrasekaran Ronen Eldan J. Gehrke Eric Horvitz ... Scott M. Lundberg Harsha Nori Hamid Palangi Marco Tulio Ribeiro Yi Zhang ELM AI4MH AI4CE ALM 230 2,989 0 22 Mar 2023
SGD learning on neural networks: leap complexity and saddle-to-saddle dynamics Emmanuel Abbe Enric Boix-Adserà Theodor Misiakiewicz FedML MLT 79 72 0 21 Feb 2023
In-context Learning and Induction Heads Catherine Olsson Nelson Elhage Neel Nanda Nicholas Joseph Nova Dassarma ... Tom B. Brown Jack Clark Jared Kaplan Sam McCandlish C. Olah 240 456 0 24 Sep 2022
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 44 89 0 25 Feb 2021
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 196 1,363 0 06 Jun 2016