高效训练论文趋势 2023–2026

Scaling law、MoE、蒸馏与训练效率

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 1,765 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

高效训练论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023112678384346
2024207812280300
202519012611882516
2026177148169109603

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

全部高效训练论文

共 499 篇,第 2 / 10 页

  1. NeurIPS 2026Efficient Fine-Tuning for Structured Sparsity Under Group Repartitioning
  2. NeurIPS 2026Efficient Image Synthesis with Sphere Latent Encoder
  3. NeurIPS 2026Efficient Label Distribution Inference Attack and Defense on Classifier Weights in Federated Learning
  4. NeurIPS 2026Efficient Learning of Truncated Boolean Product Distributions: Influence to the Rescue
  5. NeurIPS 2026Efficient LLM Adaptation with Forward-Only Passes
  6. NeurIPS 2026Efficient Memory Crystallization for Graph Learning under Non-Stationary Distribution Shifts
  7. NeurIPS 2026Efficient Pre-Training with Token Superposition
  8. NeurIPS 2026Efficient Scaling of LLM Training with Flexible Context Parallelism
  9. NeurIPS 2026Efficient Serving for Dynamic Agent Workflows with Prediction-based KV-Cache Management
  10. NeurIPS 2026Efficient Training of Deep Spiking Neural Networks with Input-Driven Derivative-Free Updates
  11. NeurIPS 2026Efficient Variational Inference for Log-Gaussian Cox Processes via Voronoi Tessellation
  12. NeurIPS 2026Efficient, Accurate and Stable Gradients for Neural ODEs
  13. NeurIPS 2026Efficiently Aligning Draft Models via Parameter- and Data-Efficient Adaptation
  14. NeurIPS 2026EngramState: Loadable Tool Priors for Efficient Function Calling
  15. NeurIPS 2026EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning
  16. NeurIPS 2026Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction
  17. NeurIPS 2026FELPS: Fair and Efficient Scheduling for Multi-LoRA Serving System
  18. NeurIPS 2026Finite-Memory Control of POMDPs: Fundamental Limits and Efficient Design
  19. NeurIPS 2026Finite-Sample and Communication-Efficient Networked Information Aggregation
  20. NeurIPS 2026Flash-KMeans: Fast and Memory-Efficient Exact K-Means
  21. NeurIPS 2026FlashMask-3: Efficient and Expressive Mask-Aware Distributed Attention
  22. NeurIPS 2026Flow-Direct: Feedback-Efficient and Reusable Guidance for Flow Models via Non-Parametric Guidance Field
  23. NeurIPS 2026From Experts to Sub-experts: Fine-grained Parameter-Efficient Fine-Tuning for MoE LLMs
  24. NeurIPS 2026Generative Cross-Entropy: A Strictly Proper Loss for Data-Efficient Classification
  25. NeurIPS 2026GramStatTexNet: Efficient, Interpretable, and Neuro-Inspired Texture Analysis-by-Synthesis
  26. NeurIPS 2026HetCCL: Efficient LLM Training on Heterogeneous Vendor GPUs
  27. NeurIPS 2026HiFloat4 Format for Language Model Pre-training on Ascend NPUs
  28. NeurIPS 2026Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization
  29. NeurIPS 2026How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models
  30. NeurIPS 2026Human-Inspired, Task-Dimension-Guided Exploration for Efficient Learning and Transfer in High Dimensions
  31. NeurIPS 2026Hyperbolic Language Models: From Zipf to Compute-Optimal Scaling
  32. NeurIPS 2026HyperVAttention: Efficient Sparse Attention with Spatio-Temporal Clustering for Video Diffusion
  33. NeurIPS 2026IncAgg: Efficient Memory-Enhanced Graph Learning via Incremental Aggregation
  34. NeurIPS 2026Joint Sequence--Vocabulary Selection for Efficient LLM Distillation
  35. NeurIPS 2026Label-Efficient Dataset Pruning via Semi-Supervised Pseudo-Labeling
  36. NeurIPS 2026Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation
  37. NeurIPS 2026Leech Lattice Vector Quantization for Efficient LLM Compression
  38. NeurIPS 2026LEMON-ZEST: Evolution-Informed Tokenization for Efficient Protein Language Modeling
  39. NeurIPS 2026LIME: Link-based User-item Interaction Modeling with Decoupled XOR Attention for Efficient Test Time Scaling
  40. NeurIPS 2026LLM Routing Through the Lens of Recommendation: A Roadmap for Efficient AI Orchestration
  41. NeurIPS 2026Logical Distillation of Transformer Encoders
  42. NeurIPS 2026LoopPrune: Evolutionary Module Selection with Iterative Execution for Efficient Large Language Model Compression
  43. NeurIPS 2026Magnitude-preserving Layers Enable Efficient GANs
  44. NeurIPS 2026Map-Guided Caching: A Global Perspective for Efficient Diffusion Transformer
  45. NeurIPS 2026Matched-Control Tests of Partition-Source Claims in One Routed Distillation Family
  46. NeurIPS 2026MemForest: Efficient Agent Memory Management via EventTree Partitioning and Progressive Merging
  47. NeurIPS 2026Meta-memorization and memorization scaling laws in transformers
  48. NeurIPS 2026MGMem: An Efficient, Deterministic, and Provenance-Preserving Framework for Long-Horizon Agent Memory
  49. NeurIPS 2026Mixture-of-Top-$k$ Attention: Efficient Attention as Scalable Fast Weights
  50. NeurIPS 2026MoE-SpAc: Efficient MoE Inference Based on Speculative Activation Utility in Heterogeneous Edge Scenario

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 查高效训练在 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": "efficient-training"}

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高效训练论文?
共 1,765 篇,按年份分别是 2023 年 346 篇、2024 年 300 篇、2025 年 516 篇、2026 年 603 篇。
NeurIPS 2026 有多少篇高效训练论文?
NeurIPS 2026 有 177 篇高效训练论文,上一届是 190 篇。
ICLR 2026 有多少篇高效训练论文?
ICLR 2026 有 148 篇高效训练论文,上一届是 126 篇。
ICML 2026 有多少篇高效训练论文?
ICML 2026 有 169 篇高效训练论文,上一届是 118 篇。
CVPR 2026 有多少篇高效训练论文?
CVPR 2026 有 109 篇高效训练论文,上一届是 82 篇。
哪个会议的高效训练论文最多?
NeurIPS,2023–2026 年共 499 篇。

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