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

184 papers, page 4 of 4

151. ICML 2024On the Embedding Collapse when Scaling up Recommendation Models
152. ICML 2024Position: Will we run out of data? Limits of LLM scaling based on human-generated data
153. ICML 2024Provably Scalable Black-Box Variational Inference with Structured Variational Families
154. ICML 2024Random Scaling and Momentum for Non-smooth Non-convex Optimization
155. ICML 2024RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
156. ICML 2024Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
157. ICML 2024Scaling Down Deep Learning with MNIST-1D
158. ICML 2024Scaling Exponents Across Parameterizations and Optimizers
159. ICML 2024Scaling Laws for Fine-Grained Mixture of Experts
160. ICML 2024Scaling Laws for the Value of Individual Data Points in Machine Learning
161. ICML 2024Scaling Tractable Probabilistic Circuits: A Systems Perspective
162. ICML 2024Selecting Large Language Model to Fine-tune via Rectified Scaling Law
163. ICML 2024SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching
164. ICML 2024SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models
165. ICML 2024Testing the Feasibility of Linear Programs with Bandit Feedback
166. ICML 2024Training-Free Long-Context Scaling of Large Language Models
167. ICML 2024Wukong: Towards a Scaling Law for Large-Scale Recommendation
168. ICML 2023Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels
169. ICML 2023Data Efficient Neural Scaling Law via Model Reusing
170. ICML 2023Dissecting the Effects of SGD Noise in Distinct Regimes of Deep Learning
171. ICML 2023Hidden Symmetries of ReLU Networks
172. ICML 2023Learning Physical Models that Can Respect Conservation Laws
173. ICML 2023Long Horizon Temperature Scaling
174. ICML 2023On the Convergence Rate of Gaussianization with Random Rotations
175. ICML 2023Online Platt Scaling with Calibeating
176. ICML 2023Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
177. ICML 2023Scaling Laws for Generative Mixed-Modal Language Models
178. ICML 2023Scaling Laws for Multilingual Neural Machine Translation
179. ICML 2023Scaling Laws for Reward Model Overoptimization
180. ICML 2023Scaling of Class-wise Training Losses for Post-hoc Calibration
181. ICML 2023Scaling Spherical CNNs
182. ICML 2023Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory
183. ICML 2023TAN Without a Burn: Scaling Laws of DP-SGD
184. ICML 2023The case for 4-bit precision: k-bit Inference Scaling Laws

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.