缩放定律论文趋势 2023–2026

主要结论

• 缩放定律论文从 2023 年的 60 篇增长到 2026 年的 248 篇，三年间扩大到约 4.1 倍。
• NeurIPS 是发缩放定律论文最多的会议，2023–2026 年共 221 篇，占四个会议总量的 37%。
• 交叉方向里涨得最快的是时间序列：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 24 篇。
• 在「优化与缩放」的 5 个主题里，它的 2026 年论文数排第 5；同组增长最快的低秩适配是 3.0 倍，缩放定律是 4.1 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部缩放定律论文

共 150 篇，第 3 / 3 页

101. ICLR 2025Scaling and evaluating sparse autoencoders
102. ICLR 2025Scaling Autonomous Agents via Automatic Reward Modeling And Planning
103. ICLR 2025Scaling Diffusion Language Models via Adaptation from Autoregressive Models
104. ICLR 2025Scaling FP8 training to trillion-token LLMs
105. ICLR 2025Scaling Laws for Adversarial Attacks on Language Model Activations and Tokens
106. ICLR 2025Scaling Laws for Downstream Task Performance in Machine Translation
107. ICLR 2025Scaling Laws for Precision
108. ICLR 2025Scaling Long Context Training Data by Long-Distance Referrals
109. ICLR 2025Scaling Optimal LR Across Token Horizons
110. ICLR 2025Scaling Stick-Breaking Attention: An Efficient Implementation and In-depth Study
111. ICLR 2025Scaling up Masked Diffusion Models on Text
112. ICLR 2025Scaling Wearable Foundation Models
113. ICLR 2025SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
114. ICLR 2025Strong Model Collapse
115. ICLR 2025Surprising Effectiveness of pretraining Ternary Language Model at Scale
116. ICLR 2025The Journey Matters: Average Parameter Count over Pre-training Unifies Sparse and Dense Scaling Laws
117. ICLR 2025TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters
118. ICLR 2025Towards Neural Scaling Laws for Time Series Foundation Models
119. ICLR 2025Transformers Struggle to Learn to Search
120. ICLR 2025U-shaped and Inverted-U Scaling behind Emergent Abilities of Large Language Models
121. ICLR 2025Ultra-Sparse Memory Network
122. ICLR 2024Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
123. ICLR 2024EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
124. ICLR 2024Generalization error of spectral algorithms
125. ICLR 2024Lagrangian Flow Networks for Conservation Laws
126. ICLR 2024Language Modeling Is Compression
127. ICLR 2024Mitigating Emergent Robustness Degradation while Scaling Graph Learning
128. ICLR 2024On the Limitations of Temperature Scaling for Distributions with Overlaps
129. ICLR 2024Principled Architecture-aware Scaling of Hyperparameters
130. ICLR 2024Scaling Convex Neural Networks with Burer-Monteiro Factorization
131. ICLR 2024Scaling Laws for Associative Memories
132. ICLR 2024Scaling Laws for Sparsely-Connected Foundation Models
133. ICLR 2024Scaling Laws of RoPE-based Extrapolation
134. ICLR 2024Scaling Supervised Local Learning with Augmented Auxiliary Networks
135. ICLR 2024The Cost of Scaling Down Large Language Models: Reducing Model Size Affects Memory before In-context Learning
136. ICLR 2024When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
137. ICLR 2023Block and Subword-Scaling Floating-Point (BSFP) : An Efficient Non-Uniform Quantization For Low Precision Inference
138. ICLR 2023Broken Neural Scaling Laws
139. ICLR 2023Distributionally Robust Post-hoc Classifiers under Prior Shifts
140. ICLR 2023How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
141. ICLR 2023Massively Scaling Heteroscedastic Classifiers
142. ICLR 2023More ConvNets in the 2020s: Scaling up Kernels Beyond 51x51 using Sparsity
143. ICLR 2023Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
144. ICLR 2023Reparameterization through Spatial Gradient Scaling
145. ICLR 2023Scaling Forward Gradient With Local Losses
146. ICLR 2023Scaling Laws For Deep Learning Based Image Reconstruction
147. ICLR 2023Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation
148. ICLR 2023Scaling Up Probabilistic Circuits by Latent Variable Distillation
149. ICLR 2023The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes
150. ICLR 2023Unsupervised Manifold Alignment with Joint Multidimensional Scaling

常见问题

2023–2026 年四大会议一共有多少篇缩放定律论文？

共 605 篇，按年份分别是 2023 年 60 篇、2024 年 96 篇、2025 年 201 篇、2026 年 248 篇。

NeurIPS 2026 有多少篇缩放定律论文？

NeurIPS 2026 有 82 篇缩放定律论文，上一届是 80 篇。

ICLR 2026 有多少篇缩放定律论文？

ICLR 2026 有 73 篇缩放定律论文，上一届是 48 篇。

ICML 2026 有多少篇缩放定律论文？

ICML 2026 有 78 篇缩放定律论文，上一届是 56 篇。

CVPR 2026 有多少篇缩放定律论文？

CVPR 2026 有 15 篇缩放定律论文，上一届是 17 篇。

哪个会议的缩放定律论文最多？

NeurIPS，2023–2026 年共 221 篇。