Transformer Working Memory Enables Regular Language Reasoning and Natural Language Length Extrapolation

5 May 2023

Papers citing "Transformer Working Memory Enables Regular Language Reasoning and Natural Language Length Extrapolation"

5 / 5 papers shown

Title
Investigating Recurrent Transformers with Dynamic Halt Jishnu Ray Chowdhury Cornelia Caragea 34 1 0 01 Feb 2024
Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto Samuel L. Smith Albert Gu Anushan Fernando Çağlar Gülçehre Razvan Pascanu Soham De 88 265 0 11 Mar 2023
Neural Networks and the Chomsky Hierarchy Grégoire Delétang Anian Ruoss Jordi Grau-Moya Tim Genewein L. Wenliang ... Chris Cundy Marcus Hutter Shane Legg Joel Veness Pedro A. Ortega UQCV 96 129 0 05 Jul 2022
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 320 8,448 0 28 Jan 2022
Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation Ofir Press Noah A. Smith M. Lewis 245 695 0 27 Aug 2021