{"total":26,"rows":[{"id":"2111.09259","title":"Acquisition of Chess Knowledge in AlphaZero","created":"2021-11-17","cited_by_count":123,"area":null},{"id":"2210.03310","title":"Scaling Forward Gradient With Local Losses","created":"2022-10-07","cited_by_count":65,"area":null},{"id":"2506.05233","title":"MesaNet: Sequence Modeling by Locally Optimal Test-Time Training","created":"2025-06-05","cited_by_count":47,"area":null},{"id":"2207.10430","title":"The Neural Race Reduction: Dynamics of Abstraction in Gated Networks","created":"2022-07-21","cited_by_count":37,"area":null},{"id":"2201.00042","title":"Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments","created":"2021-12-31","cited_by_count":25,"area":null},{"id":"2210.02157","title":"The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks","created":"2022-10-05","cited_by_count":19,"area":null},{"id":"2210.17449","title":"Globally Gated Deep Linear Networks","created":"2022-10-31","cited_by_count":12,"area":null},{"id":"2310.18885","title":"A foundational neural operator that continuously learns without forgetting","created":"2023-10-29","cited_by_count":11,"area":null},{"id":"2301.00141","title":"Self-Activating Neural Ensembles for Continual Reinforcement Learning","created":"2022-12-31","cited_by_count":7,"area":null},{"id":"2305.16945","title":"Levin Tree Search with Context Models","created":"2023-05-26","cited_by_count":7,"area":null},{"id":"2101.03419","title":"Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods","created":"2021-01-09","cited_by_count":5,"area":null},{"id":"2301.07635","title":"Local Learning with Neuron Groups","created":"2023-01-18","cited_by_count":4,"area":null},{"id":"2202.02649","title":"The Implicit Bias of Gradient Descent on Generalized Gated Linear Networks","created":"2022-02-05","cited_by_count":3,"area":null},{"id":"2504.21239","title":"Memorization and Knowledge Injection in Gated LLMs","created":"2025-04-30","cited_by_count":3,"area":null},{"id":"2507.07907","title":"A statistical physics framework for optimal learning","created":"2025-07-10","cited_by_count":3,"area":null},{"id":"2106.09776","title":"Adapting the Function Approximation Architecture in Online Reinforcement Learning","created":"2021-06-17","cited_by_count":2,"area":null},{"id":"2407.00957","title":"Expressivity of Neural Networks with Random Weights and Learned Biases","created":"2024-07-01","cited_by_count":2,"area":null},{"id":"2111.05123","title":"Gated Linear Model induced U-net for surrogate modeling and uncertainty quantification","created":"2021-11-08","cited_by_count":1,"area":null},{"id":"2203.16455","title":"Explicitising The Implicit Intrepretability of Deep Neural Networks Via Duality","created":"2022-03-01","cited_by_count":1,"area":null},{"id":"2310.07885","title":"Leader-Follower Neural Networks with Local Error Signals Inspired by Complex Collectives","created":"2023-10-11","cited_by_count":1,"area":null},{"id":"2603.11946","title":"Geometry-Aware Probabilistic Circuits via Voronoi Tessellations","created":"2026-03-12","cited_by_count":1,"area":null},{"id":"2605.03430","title":"DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data","created":"2026-05-05","cited_by_count":1,"area":null},{"id":"2109.15147","title":"Reinforcement Learning with Information-Theoretic Actuation","created":"2021-09-30","cited_by_count":0,"area":null},{"id":"2111.10622","title":"SPINE: Soft Piecewise Interpretable Neural Equations","created":"2021-11-20","cited_by_count":0,"area":null},{"id":"2305.13063","title":"Hierarchical Partitioning Forecaster","created":"2023-05-22","cited_by_count":0,"area":null},{"id":"2606.24722","title":"Decentralised AI Training and Inference with BlockTrain","created":"2026-06-23","cited_by_count":0,"area":null}],"next_cursor":null}