Don't throw the baby out with the bathwater: How and why deep learning for ARC

17 June 2025

Papers citing "Don't throw the baby out with the bathwater: How and why deep learning for ARC"

17 / 17 papers shown

Title
How Does Code Pretraining Affect Language Model Task Performance? Jackson Petty Sjoerd van Steenkiste Tal Linzen 99 13 0 06 Sep 2024
Neural networks for abstraction and reasoning: Towards broad generalization in machines Mikel Bober-Irizar Soumya Banerjee AI4CE LRM NAI 72 10 0 05 Feb 2024
Solving ARC visual analogies with neural embeddings and vector arithmetic: A generalized method Luca H. Thoms Karel A. Veldkamp Hannes Rosenbusch Claire E. Stevenson DML 75 6 0 14 Nov 2023
Hypothesis Search: Inductive Reasoning with Language Models Ruocheng Wang E. Zelikman Gabriel Poesia Yewen Pu Nick Haber Noah D. Goodman ReLM LRM 96 112 0 11 Sep 2023
General-Purpose In-Context Learning by Meta-Learning Transformers Louis Kirsch James Harrison Jascha Narain Sohl-Dickstein Luke Metz 101 78 0 08 Dec 2022
Language Models of Code are Few-Shot Commonsense Learners Aman Madaan Shuyan Zhou Uri Alon Yiming Yang Graham Neubig ReLM LRM 116 221 0 13 Oct 2022
Competition-Level Code Generation with AlphaCode Yujia Li David Choi Junyoung Chung Nate Kushman Julian Schrittwieser ... Esme Sutherland Robson Pushmeet Kohli Nando de Koray Kavukcuoglu Oriol Vinyals 143 1,413 0 08 Feb 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 823 9,576 0 28 Jan 2022
LongT5: Efficient Text-To-Text Transformer for Long Sequences Mandy Guo Joshua Ainslie David C. Uthus Santiago Ontanon Jianmo Ni Yun-hsuan Sung Yinfei Yang VLM 65 316 0 15 Dec 2021
LoRA: Low-Rank Adaptation of Large Language Models J. E. Hu Yelong Shen Phillip Wallis Zeyuan Allen-Zhu Yuanzhi Li Shean Wang Lu Wang Weizhu Chen OffRL AI4TS AI4CE ALM AIMat 477 10,496 0 17 Jun 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 667 41,369 0 22 Oct 2020
The Pitfalls of Simplicity Bias in Neural Networks Harshay Shah Kaustav Tamuly Aditi Raghunathan Prateek Jain Praneeth Netrapalli AAML 69 361 0 13 Jun 2020
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 608 4,893 0 23 Jan 2020
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 450 20,298 0 23 Oct 2019
Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML Aniruddh Raghu M. Raghu Samy Bengio Oriol Vinyals 303 646 0 19 Sep 2019
Prototypical Networks for Few-shot Learning Jake C. Snell Kevin Swersky R. Zemel 303 8,145 0 15 Mar 2017
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 373 7,333 0 13 Jun 2016