Understanding Addition in Transformers

19 October 2023

Papers citing "Understanding Addition in Transformers"

9 / 9 papers shown

Title
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges Nayoung Lee Ziyang Cai Avi Schwarzschild Kangwook Lee Dimitris Papailiopoulos ReLM VLM LRM AI4CE 127 7 0 03 Feb 2025
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis Weronika Ormaniec Felix Dangel Sidak Pal Singh 110 7 0 14 Oct 2024
Talking Heads: Understanding Inter-layer Communication in Transformer Language Models Jack Merullo Carsten Eickhoff Ellie Pavlick 111 15 0 13 Jun 2024
Large Language Models Michael R Douglas LLMAG LM&MA 138 628 0 11 Jul 2023
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks Tilman Raukur A. Ho Stephen Casper Dylan Hadfield-Menell AAML AI4CE 93 132 0 27 Jul 2022
Locating and Editing Factual Associations in GPT Kevin Meng David Bau A. Andonian Yonatan Belinkov KELM 248 1,357 0 10 Feb 2022
Transformer Feed-Forward Layers Are Key-Value Memories Mor Geva R. Schuster Jonathan Berant Omer Levy KELM 155 828 0 29 Dec 2020
Creative AI Through Evolutionary Computation Risto Miikkulainen 37 20 0 12 Jan 2019
Network Dissection: Quantifying Interpretability of Deep Visual Representations David Bau Bolei Zhou A. Khosla A. Oliva Antonio Torralba MILM FAtt 146 1,515 1 19 Apr 2017