{"total":28,"rows":[{"id":"2311.18817","title":"Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking","created":"2023-11-30","cited_by_count":80,"area":null},{"id":"2407.12332","title":"Why Do You Grok? A Theoretical Analysis of Grokking Modular Addition","created":"2024-07-17","cited_by_count":36,"area":null},{"id":"2405.06107","title":"Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory","created":"2024-05-09","cited_by_count":18,"area":null},{"id":"2411.02083","title":"Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language Models","created":"2024-11-04","cited_by_count":13,"area":null},{"id":"2410.07041","title":"Emergent properties with repeated examples","created":"2024-10-09","cited_by_count":11,"area":null},{"id":"2601.19791","title":"To Grok Grokking: Provable Grokking in Ridge Regression","created":"2026-01-27","cited_by_count":8,"area":null},{"id":"2311.12904","title":"Learning to Compute Gr\\\"obner Bases","created":"2023-11-21","cited_by_count":7,"area":null},{"id":"2510.06824","title":"Efficient numeracy in language models through single-token number embeddings","created":"2025-10-08","cited_by_count":7,"area":null},{"id":"2405.19973","title":"A Triumvirate of AI Driven Theoretical Discovery","created":"2024-05-30","cited_by_count":5,"area":null},{"id":"2408.09414","title":"Clustering and Alignment: Understanding the Training Dynamics in Modular Addition","created":"2024-08-18","cited_by_count":5,"area":null},{"id":"2410.03569","title":"Making Hard Problems Easier with Custom Data Distributions and Loss Regularization: A Case Study in Modular Arithmetic","created":"2024-10-04","cited_by_count":4,"area":null},{"id":"2405.16658","title":"Acceleration of Grokking in Learning Arithmetic Operations via Kolmogorov-Arnold Representation","created":"2024-05-26","cited_by_count":3,"area":null},{"id":"2504.16760","title":"Lightweight Latent Verifiers for Efficient Meta-Generation Strategies","created":"2025-04-23","cited_by_count":3,"area":null},{"id":"2506.23286","title":"Not All Explanations for Deep Learning Phenomena Are Equally Valuable","created":"2025-06-29","cited_by_count":3,"area":null},{"id":"2511.12421","title":"From Black Box to Bijection: Interpreting Machine Learning to Build a Zeta Map Algorithm","created":"2025-11-16","cited_by_count":3,"area":null},{"id":"2604.13082","title":"The Long Delay to Arithmetic Generalization: When Learned Representations Outrun Behavior","created":"2026-03-30","cited_by_count":3,"area":null},{"id":"2410.23948","title":"Transformers to Predict the Applicability of Symbolic Integration Routines","created":"2024-10-31","cited_by_count":2,"area":null},{"id":"2408.00197","title":"Automated Software Vulnerability Static Code Analysis Using Generative Pre-Trained Transformer Models","created":"2024-07-31","cited_by_count":1,"area":null},{"id":"2410.24050","title":"A Mechanistic Study of Transformers Training Dynamics","created":"2024-10-31","cited_by_count":1,"area":null},{"id":"2501.09729","title":"Generating particle physics Lagrangians with transformers","created":"2025-01-16","cited_by_count":1,"area":null},{"id":"2502.10335","title":"Studying number theory with deep learning: a case study with the M\\\"obius and squarefree indicator functions","created":"2025-02-14","cited_by_count":1,"area":null},{"id":"2502.17513","title":"Int2Int: a framework for mathematics with transformers","created":"2025-02-22","cited_by_count":1,"area":null},{"id":"2506.23875","title":"Discovering Learning-Friendly Generation Orders for Sequential Computation","created":"2025-06-30","cited_by_count":1,"area":null},{"id":"2602.04548","title":"Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions","created":"2026-02-04","cited_by_count":1,"area":null},{"id":"2410.16484","title":"Identifying Sub-networks in Neural Networks via Functionally Similar Representations","created":"2024-10-21","cited_by_count":0,"area":null},{"id":"2506.20305","title":"Learning Moderately Input-Sensitive Functions: A Case Study in QR Code Decoding","created":"2025-06-25","cited_by_count":0,"area":null},{"id":"2605.14659","title":"Slower Generalization, Faster Memorization: A Sweet Spot in Algorithmic Learning","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2605.21160","title":"Learning First Integrals via Backward-Generated Data and Guided Reinforcement Learning","created":"2026-05-20","cited_by_count":0,"area":null}],"next_cursor":null}