{"total":24,"rows":[{"id":"2411.00566","title":"PatternBoost: Constructions in Mathematics with a Little Help from AI","created":"2024-11-01","cited_by_count":34,"area":null},{"id":"2411.11910","title":"AIGS: Generating Science from AI-Powered Automated Falsification","created":"2024-11-17","cited_by_count":18,"area":null},{"id":"2507.11737","title":"Auto-Formulating Dynamic Programming Problems with Large Language Models","created":"2025-07-15","cited_by_count":16,"area":null},{"id":"2602.24173","title":"LemmaBench: A Live, Research-Level Benchmark to Evaluate LLM Capabilities in Mathematics","created":"2026-02-27","cited_by_count":10,"area":null},{"id":"2507.03732","title":"Transforming Calabi-Yau Constructions: Generating New Calabi-Yau Manifolds with Transformers","created":"2025-07-04","cited_by_count":5,"area":null},{"id":"2411.06833","title":"Learning Interpretable Network Dynamics via Universal Neural Symbolic Regression","created":"2024-11-11","cited_by_count":4,"area":null},{"id":"2501.18527","title":"Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?","created":"2025-01-30","cited_by_count":4,"area":null},{"id":"2504.12465","title":"Geometric Generality of Transformer-Based Gr\\\"obner Basis Computation","created":"2025-04-16","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":"2601.18005","title":"Flow-based Extremal Mathematical Structure Discovery","created":"2026-01-25","cited_by_count":3,"area":null},{"id":"2601.21150","title":"Can Neural Networks Learn Small Algebraic Worlds? An Investigation Into the Group-theoretic Structures Learned By Narrow Models Trained To Predict Group Operations","created":"2026-01-29","cited_by_count":3,"area":null},{"id":"2503.09730","title":"Local Look-Ahead Guidance via Verifier-in-the-Loop for Automated Theorem Proving","created":"2025-03-12","cited_by_count":2,"area":null},{"id":"2502.17513","title":"Int2Int: a framework for mathematics with transformers","created":"2025-02-22","cited_by_count":1,"area":null},{"id":"2505.17964","title":"Counting Cycles with AI: Counting Cycles with AI: Computationally Efficient Equivalent Forms with Applications","created":"2025-05-23","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":"2509.19162","title":"CayleyPy Growth: Efficient growth computations and hundreds of new conjectures on Cayley graphs (Brief version)","created":"2025-09-23","cited_by_count":1,"area":null},{"id":"2605.19063","title":"Mapping Uncharted Symmetries: Machine Discovery in Combinatorics","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2506.08600","title":"CALT: A Library for Computer Algebra with Transformer","created":"2025-06-10","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":"2602.07800","title":"Approximating Matrix Functions with Deep Neural Networks and Transformers","created":"2026-02-08","cited_by_count":0,"area":null},{"id":"2605.01072","title":"Reconstructing conformal field theoretical compositions with Transformers","created":"2026-05-01","cited_by_count":0,"area":null},{"id":"2605.07648","title":"Learning Large-Scale Modular Addition with an Auxiliary Modulus","created":"2026-05-08","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},{"id":"2606.26660","title":"Generating Special Triangulations with Transformers","created":"2026-06-25","cited_by_count":0,"area":null}],"next_cursor":null}