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 201 篇，第 4 / 5 页

  1. NeurIPS 2025Is Limited Participant Diversity Impeding EEG-based Machine Learning?
  2. NeurIPS 2025Kinetics: Rethinking Test-Time Scaling Law
  3. NeurIPS 2025L$^2$M: Mutual Information Scaling Law for Long-Context Language Modeling
  4. NeurIPS 2025LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thought
  5. NeurIPS 2025Learning in Compact Spaces with Approximately Normalized Transformer
  6. NeurIPS 2025Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
  7. NeurIPS 2025Meta CLIP 2: A Worldwide Scaling Recipe
  8. NeurIPS 2025Mind the GAP! The Challenges of Scale in Pixel-based Deep Reinforcement Learning
  9. NeurIPS 2025NaViL: Rethinking Scaling Properties of Native Multimodal Large Language Models under Data Constraints
  10. NeurIPS 2025NAVIX: Scaling MiniGrid Environments with JAX
  11. NeurIPS 2025On the Entropy Calibration of Language Models
  12. NeurIPS 2025On the Surprising Effectiveness of Large Learning Rates under Standard Width Scaling
  13. NeurIPS 2025Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
  14. NeurIPS 2025Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling
  15. NeurIPS 2025P-Law: Predicting Quantitative Scaling Law with Entropy Guidance in Large Recommendation Models
  16. NeurIPS 2025Parallel Scaling Law for Language Models
  17. NeurIPS 2025ParetoQ: Improving Scaling Laws in Extremely Low-bit LLM Quantization
  18. NeurIPS 2025Power Lines: Scaling laws for weight decay and batch size in LLM pre-training
  19. NeurIPS 2025Predictable Scale (Part II) --- Farseer: A Refined Scaling Law in LLMs
  20. NeurIPS 2025Provable Scaling Laws for the Test-Time Compute of Large Language Models
  21. NeurIPS 2025Recursive Inference Scaling: A Winning Path to Scalable Inference in Language and Multimodal Systems
  22. NeurIPS 2025Remasking Discrete Diffusion Models with Inference-Time Scaling
  23. NeurIPS 2025RigAnyFace: Scaling Neural Facial Mesh Auto-Rigging with Unlabeled Data
  24. NeurIPS 2025RoMA: Scaling up Mamba-based Foundation Models for Remote Sensing
  25. NeurIPS 2025Routing Mamba: Scaling State Space Models with Mixture-of-Experts Projection
  26. NeurIPS 2025Scaling and context steer LLMs along the same computational path as the human brain
  27. NeurIPS 2025Scaling can lead to compositional generalization
  28. NeurIPS 2025Scaling Embedding Layers in Language Models
  29. NeurIPS 2025Scaling Epidemic Inference on Contact Networks: Theory and Algorithms
  30. NeurIPS 2025Scaling Image Geo-Localization to Continent Level
  31. NeurIPS 2025Scaling Language-centric Omnimodal Representation Learning
  32. NeurIPS 2025Scaling Law with Learning Rate Annealing
  33. NeurIPS 2025Scaling Laws for Gradient Descent and Sign Descent for Linear Bigram Models under Zipf’s Law
  34. NeurIPS 2025Scaling Laws for Optimal Data Mixtures
  35. NeurIPS 2025Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets
  36. NeurIPS 2025Scaling Laws For Scalable Oversight
  37. NeurIPS 2025Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
  38. NeurIPS 2025Scaling Offline RL via Efficient and Expressive Shortcut Models
  39. NeurIPS 2025Scaling Speculative Decoding with Lookahead Reasoning
  40. NeurIPS 2025Scaling Unlocks Broader Generation and Deeper Functional Understanding of Proteins
  41. NeurIPS 2025Scaling Up Active Testing to Large Language Models
  42. NeurIPS 2025Sloth: scaling laws for LLM skills to predict multi-benchmark performance across families
  43. NeurIPS 2025Subspace Networks: Scaling Decentralized Training with Communication-Efficient Model Parallelism
  44. NeurIPS 2025Superposition Yields Robust Neural Scaling
  45. NeurIPS 2025SWE-smith: Scaling Data for Software Engineering Agents
  46. NeurIPS 2025TabDPT: Scaling Tabular Foundation Models on Real Data
  47. NeurIPS 2025The Curse of Depth in Large Language Models
  48. NeurIPS 2025Understanding LLM Behaviors via Compression: Data Generation, Knowledge Acquisition and Scaling Laws
  49. NeurIPS 2025Unified Scaling Laws for Compressed Representations
  50. NeurIPS 2025When Worse is Better: Navigating the Compression Generation Trade-off In Visual Tokenization

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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