Scaling Laws papers, 2023–2026

Key findings

• Scaling Laws went from 60 papers in 2023 to 248 in 2026, roughly 4.1x in three years.
• NeurIPS publishes the most Scaling Laws work: 221 papers from 2023 to 2026, 37% of the four-venue total.
• The fastest-growing overlap is with Time Series: papers tagged with both rose from 1 in 2023 to 24 in 2026.
• Among the 5 topics under Optimization and Scaling, it ranks #5 by 2026 paper count; the fastest grower in the group, Low-Rank Adaptation, is up 3.0x versus 4.1x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Unified Merge Calculus for Learning-Rate Scaling on Neural Computation Graphs
• ICML 2026A Capacity-Based Rationale for Multi-Head Attention
• ICLR 2026$\mathbf{Li_2}$: A Framework on Dynamics of Feature Emergence and Delayed Generalization
• CVPR 2026A Unified Framework for Knowledge Transfer in Bidirectional Model Scaling
• NeurIPS 2025Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternatives
• ICML 2025A Simple Model of Inference Scaling Laws
• ICLR 2025(Mis)Fitting Scaling Laws: A Survey of Scaling Law Fitting Techniques in Deep Learning
• CVPR 2025D^3: Scaling Up Deepfake Detection by Learning from Discrepancy
• NeurIPS 2024An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem
• ICML 2024A Dynamical Model of Neural Scaling Laws
• ICLR 2024Principled Architecture-aware Scaling of Hyperparameters
• CVPR 2024From Activation to Initialization: Scaling Insights for Optimizing Neural Fields
• NeurIPS 2023Abide by the law and follow the flow: conservation laws for gradient flows
• ICML 2023Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning
• ICLR 2023Distributionally Robust Post-hoc Classifiers under Prior Shifts
• CVPR 2023LargeKernel3D: Scaling Up Kernels in 3D Sparse CNNs
• NeurIPS 2026ADIS-Law: Unified Scaling Laws for Annealing-Phase Domain Injection in Large Language Models
• ICML 2026Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks
• ICLR 2026A universal compression theory: Lottery ticket hypothesis and superpolynomial scaling laws
• CVPR 2026MatAnyone 2 Scaling Video Matting via a Learned Quality Evaluator

All Scaling Laws papers

80 papers, page 1 of 2

1. NeurIPS 2025$\mu$PC: Scaling Predictive Coding to 100+ Layer Networks
2. NeurIPS 2025Align Your Flow: Scaling Continuous-Time Flow Map Distillation
3. NeurIPS 2025AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power Laws
4. NeurIPS 2025Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternatives
5. NeurIPS 2025Avoiding exp(R) scaling in RLHF through Preference-based Exploration
6. NeurIPS 2025BioCLIP 2: Emergent Properties from Scaling Hierarchical Contrastive Learning
7. NeurIPS 2025Can DPO Learn Diverse Human Values? A Theoretical Scaling Law
8. NeurIPS 2025Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo
9. NeurIPS 2025Complexity Scaling Laws for Neural Models using Combinatorial Optimization
10. NeurIPS 2025Compute-Optimal Scaling for Value-Based Deep RL
11. NeurIPS 2025Data Mixing Can Induce Phase Transitions in Knowledge Acquisition
12. NeurIPS 2025Data Mixture Optimization: A Multi-fidelity Multi-scale Bayesian Framework
13. NeurIPS 2025Datasets, Documents, and Repetitions: The Practicalities of Unequal Data Quality
14. NeurIPS 2025Dimension-adapted Momentum Outscales SGD
15. NeurIPS 2025DISC: Dynamic Decomposition Improves LLM Inference Scaling
16. NeurIPS 2025Does Thinking More Always Help? Mirage of Test-Time Scaling in Reasoning Models
17. NeurIPS 2025E2Former: An Efficient and Equivariant Transformer with Linear-Scaling Tensor Products
18. NeurIPS 2025Efficiently Scaling LLM Reasoning Programs with Certaindex
19. NeurIPS 2025Emergence and scaling laws in SGD learning of shallow neural networks
20. NeurIPS 2025Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback
21. NeurIPS 2025Functional Scaling Laws in Kernel Regression: Loss Dynamics and Learning Rate Schedules
22. NeurIPS 2025Gemstones: A Model Suite for Multi-Faceted Scaling Laws
23. NeurIPS 2025GeoLLaVA-8K: Scaling Remote-Sensing Multimodal Large Language Models to 8K Resolution
24. NeurIPS 2025GPAS: Accelerating Convergence of LLM Pretraining via Gradient-Preserving Activation Scaling
25. NeurIPS 2025HiFC: High-efficiency Flash-based KV Cache Swapping for Scaling LLM Inference
26. NeurIPS 2025How to Scale Second-Order Optimization
27. NeurIPS 2025Improved Scaling Laws in Linear Regression via Data Reuse
28. NeurIPS 2025Inference-Time Hyper-Scaling with KV Cache Compression
29. NeurIPS 2025Infinite-Width Limit of a Single Attention Layer: Analysis via Tensor Programs
30. NeurIPS 2025Is Limited Participant Diversity Impeding EEG-based Machine Learning?
31. NeurIPS 2025Kinetics: Rethinking Test-Time Scaling Law
32. NeurIPS 2025L$^2$M: Mutual Information Scaling Law for Long-Context Language Modeling
33. NeurIPS 2025LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thought
34. NeurIPS 2025Learning in Compact Spaces with Approximately Normalized Transformer
35. NeurIPS 2025Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
36. NeurIPS 2025Meta CLIP 2: A Worldwide Scaling Recipe
37. NeurIPS 2025Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning
38. NeurIPS 2025NaViL: Rethinking Scaling Properties of Native Multimodal Large Language Models under Data Constraints
39. NeurIPS 2025NAVIX: Scaling MiniGrid Environments with JAX
40. NeurIPS 2025On the Entropy Calibration of Language Models
41. NeurIPS 2025On the Surprising Effectiveness of Large Learning Rates under Standard Width Scaling
42. NeurIPS 2025Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
43. NeurIPS 2025Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling
44. NeurIPS 2025P-Law: Predicting Quantitative Scaling Law with Entropy Guidance in Large Recommendation Models
45. NeurIPS 2025Parallel Scaling Law for Language Models
46. NeurIPS 2025ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization
47. NeurIPS 2025Power Lines: Scaling laws for weight decay and batch size in LLM pre-training
48. NeurIPS 2025Predictable Scale (Part II) --- Farseer: A Refined Scaling Law in LLMs
49. NeurIPS 2025Provable Scaling Laws for the Test-Time Compute of Large Language Models
50. NeurIPS 2025Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems

FAQ

How many Scaling Laws papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

605 in total: 60 in 2023, 96 in 2024, 201 in 2025, 248 in 2026.

How many Scaling Laws papers are at NeurIPS 2026?

NeurIPS 2026 has 82 Scaling Laws papers, versus 80 the year before.

How many Scaling Laws papers are at ICLR 2026?

ICLR 2026 has 73 Scaling Laws papers, versus 48 the year before.

How many Scaling Laws papers are at ICML 2026?

ICML 2026 has 78 Scaling Laws papers, versus 56 the year before.

How many Scaling Laws papers are at CVPR 2026?

CVPR 2026 has 15 Scaling Laws papers, versus 17 the year before.

Which conference publishes the most Scaling Laws papers?

NeurIPS, with 221 papers from 2023 to 2026.