Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with
Recurrent Networks

Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks

8 June 2021

Avi Schwarzschild

Furong Huang

Papers citing "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks"

10 / 60 papers shown

Title
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes Shivam Garg Dimitris Tsipras Percy Liang Gregory Valiant 26 449 0 01 Aug 2022
FLOWGEN: Fast and slow graph generation Aman Madaan Yiming Yang AI4CE 19 3 0 15 Jul 2022
Exploring Length Generalization in Large Language Models Cem Anil Yuhuai Wu Anders Andreassen Aitor Lewkowycz Vedant Misra V. Ramasesh Ambrose Slone Guy Gur-Ari Ethan Dyer Behnam Neyshabur ReLM LRM 33 158 0 11 Jul 2022
Learning Iterative Reasoning through Energy Minimization Yilun Du Shuang Li J. Tenenbaum Igor Mordatch PINN 33 23 0 30 Jun 2022
Short-Term Plasticity Neurons Learning to Learn and Forget Hector Garcia Rodriguez Qinghai Guo Timoleon Moraitis 13 12 0 28 Jun 2022
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models Denny Zhou Nathanael Scharli Le Hou Jason W. Wei Nathan Scales ... Dale Schuurmans Claire Cui Olivier Bousquet Quoc Le Ed H. Chi RALM LRM AI4CE 12 1,043 0 21 May 2022
End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking Arpit Bansal Avi Schwarzschild Eitan Borgnia Z. Emam Furong Huang Micah Goldblum Tom Goldstein LRM 11 24 0 11 Feb 2022
Tutorial on amortized optimization Brandon Amos OffRL 75 43 0 01 Feb 2022
Combinatorial optimization and reasoning with graph neural networks Quentin Cappart Didier Chételat Elias Boutros Khalil Andrea Lodi Christopher Morris Petar Velickovic AI4CE 32 347 0 18 Feb 2021
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex Q. Liao T. Poggio 213 255 0 13 Apr 2016