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

605 papers, page 10 of 13

451. CVPR 2024An Empirical Study of Scaling Law for Scene Text Recognition
452. CVPR 2024DUDF: Differentiable Unsigned Distance Fields with Hyperbolic Scaling
453. CVPR 2024From Activation to Initialization: Scaling Insights for Optimizing Neural Fields
454. CVPR 2024InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks
455. CVPR 2024Scaling Laws for Data Filtering-- Data Curation cannot be Compute Agnostic
456. CVPR 2024Scaling Laws of Synthetic Images for Model Training ... for Now
457. CVPR 2024Scaling Up Dynamic Human-Scene Interaction Modeling
458. CVPR 2024Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild
459. CVPR 2024Scaling Up Video Summarization Pretraining with Large Language Models
460. ICLR 2024Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
461. ICLR 2024EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
462. ICLR 2024Generalization error of spectral algorithms
463. ICLR 2024Lagrangian Flow Networks for Conservation Laws
464. ICLR 2024Language Modeling Is Compression
465. ICLR 2024Mitigating Emergent Robustness Degradation while Scaling Graph Learning
466. ICLR 2024On the Limitations of Temperature Scaling for Distributions with Overlaps
467. ICLR 2024Principled Architecture-aware Scaling of Hyperparameters
468. ICLR 2024Scaling Convex Neural Networks with Burer-Monteiro Factorization
469. ICLR 2024Scaling Laws for Associative Memories
470. ICLR 2024Scaling Laws for Sparsely-Connected Foundation Models
471. ICLR 2024Scaling Laws of RoPE-based Extrapolation
472. ICLR 2024Scaling Supervised Local Learning with Augmented Auxiliary Networks
473. ICLR 2024The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning
474. ICLR 2024When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
475. ICML 2024A Dynamical Model of Neural Scaling Laws
476. ICML 2024A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization
477. ICML 2024A Tale of Tails: Model Collapse as a Change of Scaling Laws
478. ICML 2024Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies
479. ICML 2024Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
480. ICML 2024Data Engineering for Scaling Language Models to 128K Context
481. ICML 2024Differentiable Model Scaling using Differentiable Topk
482. ICML 2024Explorations of Self-Repair in Language Models
483. ICML 2024Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models
484. ICML 2024Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws
485. ICML 2024IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency
486. ICML 2024Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows
487. ICML 2024Mechanistic Design and Scaling of Hybrid Architectures
488. ICML 2024Mixtures of Experts Unlock Parameter Scaling for Deep RL
489. ICML 2024Navigating Scaling Laws: Compute Optimality in Adaptive Model Training
490. ICML 2024Offline Actor-Critic Reinforcement Learning Scales to Large Models
491. ICML 2024On the Embedding Collapse when Scaling up Recommendation Models
492. ICML 2024Position: Will we run out of data? Limits of LLM scaling based on human-generated data
493. ICML 2024Provably Scalable Black-Box Variational Inference with Structured Variational Families
494. ICML 2024Random Scaling and Momentum for Non-smooth Non-convex Optimization
495. ICML 2024RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
496. ICML 2024Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
497. ICML 2024Scaling Down Deep Learning with MNIST-1D
498. ICML 2024Scaling Exponents Across Parameterizations and Optimizers
499. ICML 2024Scaling Laws for Fine-Grained Mixture of Experts
500. ICML 2024Scaling Laws for the Value of Individual Data Points in Machine Learning

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.