{"total":25,"rows":[{"id":"2206.14486","title":"Beyond neural scaling laws: beating power law scaling via data pruning","created":"2022-06-29","cited_by_count":528,"area":null},{"id":"2404.05405","title":"Physics of Language Models: Part 3.3, Knowledge Capacity Scaling Laws","created":"2024-04-08","cited_by_count":144,"area":null},{"id":"2209.06640","title":"Revisiting Neural Scaling Laws in Language and Vision","created":"2022-09-13","cited_by_count":132,"area":null},{"id":"2209.03942","title":"Data Feedback Loops: Model-driven Amplification of Dataset Biases","created":"2022-09-08","cited_by_count":60,"area":null},{"id":"2303.11341","title":"What does it take to catch a Chinchilla? Verifying Rules on Large-Scale Neural Network Training via Compute Monitoring","created":"2023-03-20","cited_by_count":21,"area":null},{"id":"2303.05420","title":"Kernel Regression with Infinite-Width Neural Networks on Millions of Examples","created":"2023-03-09","cited_by_count":9,"area":null},{"id":"2411.02992","title":"Efficient and Effective Adaptation of Multimodal Foundation Models in Sequential Recommendation","created":"2024-11-05","cited_by_count":7,"area":null},{"id":"2302.03068","title":"Evaluating Self-Supervised Learning via Risk Decomposition","created":"2023-02-06","cited_by_count":6,"area":null},{"id":"2511.21622","title":"On the Origin of Algorithmic Progress in AI","created":"2025-11-26","cited_by_count":6,"area":null},{"id":"2404.02973","title":"Scaling Laws for Galaxy Images","created":"2024-04-03","cited_by_count":5,"area":null},{"id":"2411.01088","title":"CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks","created":"2024-11-02","cited_by_count":4,"area":null},{"id":"2509.20721","title":"Scaling Laws are Redundancy Laws","created":"2025-09-25","cited_by_count":3,"area":null},{"id":"2602.07238","title":"Is there \"Secret Sauce'' in Large Language Model Development?","created":"2026-02-06","cited_by_count":3,"area":null},{"id":"2508.09075","title":"Scaling Learned Image Compression Models up to 1 Billion","created":"2025-08-12","cited_by_count":2,"area":null},{"id":"2510.16743","title":"Zero-Shot Performance Prediction for Probabilistic Scaling Laws","created":"2025-10-19","cited_by_count":2,"area":null},{"id":"2207.12547","title":"The BUTTER Zone: An Empirical Study of Training Dynamics in Fully Connected Neural Networks","created":"2022-07-25","cited_by_count":1,"area":null},{"id":"2405.07226","title":"Separable Power of Classical and Quantum Learning Protocols Through the Lens of No-Free-Lunch Theorem","created":"2024-05-12","cited_by_count":1,"area":null},{"id":"2406.08933","title":"LaCoOT: Layer Collapse through Optimal Transport","created":"2024-06-13","cited_by_count":1,"area":null},{"id":"2505.23032","title":"Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks","created":"2025-05-29","cited_by_count":1,"area":null},{"id":"2509.25933","title":"From MNIST to ImageNet: Understanding the Scalability Boundaries of Differentiable Logic Gate Networks","created":"2025-09-30","cited_by_count":1,"area":null},{"id":"2212.09723","title":"MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages","created":"2022-12-19","cited_by_count":0,"area":null},{"id":"2410.06567","title":"Convex Distillation: Efficient Compression of Deep Networks via Convex Optimization","created":"2024-10-09","cited_by_count":0,"area":null},{"id":"2603.29121","title":"Economics of Human and AI Collaboration: When is Partial Automation More Attractive than Full Automation?","created":"2026-03-31","cited_by_count":0,"area":null},{"id":"2605.17234","title":"Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2607.00913","title":"Two AI Metrics Diverged: Will it Make All the Difference?","created":"2026-07-01","cited_by_count":0,"area":null}],"next_cursor":null}