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

201 papers, page 4 of 5

151. NeurIPS 2025Is Limited Participant Diversity Impeding EEG-based Machine Learning?
152. NeurIPS 2025Kinetics: Rethinking Test-Time Scaling Law
153. NeurIPS 2025L$^2$M: Mutual Information Scaling Law for Long-Context Language Modeling
154. NeurIPS 2025LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thought
155. NeurIPS 2025Learning in Compact Spaces with Approximately Normalized Transformer
156. NeurIPS 2025Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
157. NeurIPS 2025Meta CLIP 2: A Worldwide Scaling Recipe
158. NeurIPS 2025Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning
159. NeurIPS 2025NaViL: Rethinking Scaling Properties of Native Multimodal Large Language Models under Data Constraints
160. NeurIPS 2025NAVIX: Scaling MiniGrid Environments with JAX
161. NeurIPS 2025On the Entropy Calibration of Language Models
162. NeurIPS 2025On the Surprising Effectiveness of Large Learning Rates under Standard Width Scaling
163. NeurIPS 2025Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
164. NeurIPS 2025Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling
165. NeurIPS 2025P-Law: Predicting Quantitative Scaling Law with Entropy Guidance in Large Recommendation Models
166. NeurIPS 2025Parallel Scaling Law for Language Models
167. NeurIPS 2025ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization
168. NeurIPS 2025Power Lines: Scaling laws for weight decay and batch size in LLM pre-training
169. NeurIPS 2025Predictable Scale (Part II) --- Farseer: A Refined Scaling Law in LLMs
170. NeurIPS 2025Provable Scaling Laws for the Test-Time Compute of Large Language Models
171. NeurIPS 2025Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems
172. NeurIPS 2025Remasking Discrete Diffusion Models with Inference-Time Scaling
173. NeurIPS 2025RigAnyFace: Scaling Neural Facial Mesh Auto-Rigging with Unlabeled Data
174. NeurIPS 2025RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing
175. NeurIPS 2025Routing Mamba: Scaling State Space Models with Mixture-of-Experts Projection
176. NeurIPS 2025Scaling and context steer LLMs along the same computational path as the human brain
177. NeurIPS 2025Scaling can lead to compositional generalization
178. NeurIPS 2025Scaling Embedding Layers in Language Models
179. NeurIPS 2025Scaling Epidemic Inference on Contact Networks: Theory and Algorithms
180. NeurIPS 2025Scaling Image Geo-Localization to Continent Level
181. NeurIPS 2025Scaling Language-centric Omnimodal Representation Learning
182. NeurIPS 2025Scaling Law with Learning Rate Annealing
183. NeurIPS 2025Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf’s Law
184. NeurIPS 2025Scaling Laws for Optimal Data Mixtures
185. NeurIPS 2025Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets
186. NeurIPS 2025Scaling Laws For Scalable Oversight
187. NeurIPS 2025Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
188. NeurIPS 2025Scaling Offline RL via Efficient and Expressive Shortcut Models
189. NeurIPS 2025Scaling Speculative Decoding with Lookahead Reasoning
190. NeurIPS 2025Scaling Unlocks Broader Generation and Deeper Functional Understanding of Proteins
191. NeurIPS 2025Scaling Up Active Testing to Large Language Models
192. NeurIPS 2025Sloth: scaling laws for LLM skills to predict multi-benchmark performance across families
193. NeurIPS 2025Subspace Networks: Scaling Decentralized Training with Communication-Efficient Model Parallelism
194. NeurIPS 2025Superposition Yields Robust Neural Scaling
195. NeurIPS 2025SWE-smith: Scaling Data for Software Engineering Agents
196. NeurIPS 2025TabDPT: Scaling Tabular Foundation Models on Real Data
197. NeurIPS 2025The Curse of Depth in Large Language Models
198. NeurIPS 2025Understanding LLM Behaviors via Compression: Data Generation, Knowledge Acquisition and Scaling Laws
199. NeurIPS 2025Unified Scaling Laws for Compressed Representations
200. NeurIPS 2025When Worse is Better: Navigating the Compression Generation Trade-off In Visual Tokenization

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.