缩放定律论文趋势 2023–2026

数据/模型缩放

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 605 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

缩放定律论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023211417860
20243815331096
202580485617201
202682737815248

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

全部缩放定律论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 80 篇，第 1 / 2 页

  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

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查缩放定律在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？

AI 会调用的工具：get_topic_stats {"topic": "scaling-laws"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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