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Learning the greatest common divisor: explaining transformer predictions

Learning the greatest common divisor: explaining transformer predictions

29 August 2023
Franccois Charton
ArXivPDFHTML

Papers citing "Learning the greatest common divisor: explaining transformer predictions"

14 / 14 papers shown
Title
Lightweight Latent Verifiers for Efficient Meta-Generation Strategies
Lightweight Latent Verifiers for Efficient Meta-Generation Strategies
Bartosz Piotrowski
Witold Drzewakowski
Konrad Staniszewski
Piotr Miłoś
LRM
36
0
0
23 Apr 2025
Int2Int: a framework for mathematics with transformers
Int2Int: a framework for mathematics with transformers
François Charton
ViT
46
0
0
22 Feb 2025
Formal Mathematical Reasoning: A New Frontier in AI
Formal Mathematical Reasoning: A New Frontier in AI
Kaiyu Yang
Gabriel Poesia
Jingxuan He
Wenda Li
Kristin Lauter
Swarat Chaudhuri
Dawn Song
LRM
AI4CE
82
22
0
20 Dec 2024
Transformers to Predict the Applicability of Symbolic Integration
  Routines
Transformers to Predict the Applicability of Symbolic Integration Routines
Rashid Barket
Uzma Shafiq
Matthew England
Juergen Gerhard
27
0
0
31 Oct 2024
Identifying Sub-networks in Neural Networks via Functionally Similar Representations
Identifying Sub-networks in Neural Networks via Functionally Similar Representations
Tian Gao
Amit Dhurandhar
K. Ramamurthy
Dennis L. Wei
45
0
0
21 Oct 2024
Emergent properties with repeated examples
Emergent properties with repeated examples
Francois Charton
Julia Kempe
AIMat
34
2
0
09 Oct 2024
Clustering and Alignment: Understanding the Training Dynamics in Modular
  Addition
Clustering and Alignment: Understanding the Training Dynamics in Modular Addition
Tiberiu Musat
40
1
0
18 Aug 2024
Automated Software Vulnerability Static Code Analysis Using Generative
  Pre-Trained Transformer Models
Automated Software Vulnerability Static Code Analysis Using Generative Pre-Trained Transformer Models
Elijah Pelofske
Vincent Urias
L. Liebrock
46
1
0
31 Jul 2024
Why Do You Grok? A Theoretical Analysis of Grokking Modular Addition
Why Do You Grok? A Theoretical Analysis of Grokking Modular Addition
Mohamad Amin Mohamadi
Zhiyuan Li
Lei Wu
Danica J. Sutherland
48
9
0
17 Jul 2024
Acceleration of Grokking in Learning Arithmetic Operations via
  Kolmogorov-Arnold Representation
Acceleration of Grokking in Learning Arithmetic Operations via Kolmogorov-Arnold Representation
Yeachan Park
Minseok Kim
Yeoneung Kim
29
1
0
26 May 2024
Transforming the Bootstrap: Using Transformers to Compute Scattering
  Amplitudes in Planar N = 4 Super Yang-Mills Theory
Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory
Tianji Cai
G. W. Merz
Franccois Charton
Niklas Nolte
Matthias Wilhelm
K. Cranmer
Lance J. Dixon
36
15
0
09 May 2024
Opening the AI black box: program synthesis via mechanistic
  interpretability
Opening the AI black box: program synthesis via mechanistic interpretability
Eric J. Michaud
Isaac Liao
Vedang Lad
Ziming Liu
Anish Mudide
Chloe Loughridge
Zifan Carl Guo
Tara Rezaei Kheirkhah
Mateja Vukelić
Max Tegmark
23
12
0
07 Feb 2024
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce
  Grokking
Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
Kaifeng Lyu
Jikai Jin
Zhiyuan Li
Simon S. Du
Jason D. Lee
Wei Hu
AI4CE
44
32
0
30 Nov 2023
Transformer-based Machine Learning for Fast SAT Solvers and Logic
  Synthesis
Transformer-based Machine Learning for Fast SAT Solvers and Logic Synthesis
Feng Shi
Chonghan Lee
M. K. Bashar
N. Shukla
Song-Chun Zhu
N. Vijaykrishnan
NAI
LRM
39
12
0
15 Jul 2021
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