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 177 篇,第 1 / 4 页

  1. NeurIPS 2026$\delta$-Mem: : Efficient Online Memory For Large Language Models
  2. NeurIPS 2026A Grid Efficient Transport Optimization Model for the Wasserstein Barycenter Problem
  3. NeurIPS 2026A Solver-Efficient Neural Adversarial Attack on Subgraph Matching Models
  4. NeurIPS 2026Achieve Latency-Efficient Temporal-Coding Spiking LLMs via Discretization-Aware Conversion
  5. NeurIPS 2026Adapting in the Dark: Efficient and Stable Test-Time Adaptation for Black-Box Models
  6. NeurIPS 2026Adaptive Residual Quantization for Memory-Efficient Temporal Action Segmentation
  7. NeurIPS 2026ADIS-Law: Unified Scaling Laws for Annealing-Phase Domain Injection in Large Language Models
  8. NeurIPS 2026Advanced Routing as Regularization Allocation for Efficient Diffusion Transformer Training
  9. NeurIPS 2026AgentWeave: Efficient Distributed Agent Serving via Flow Decomposition
  10. NeurIPS 2026An Efficient Cross-modal Feature Reconstruction Model for Multimodal Multi-class Anomaly Detection
  11. NeurIPS 2026ASVQ: What Reparameterization Is Just Enough for Efficient Codebook Learning?
  12. NeurIPS 2026Asymmetric Scaling Laws from Sparse Features
  13. NeurIPS 2026Attribute-Efficient Learning of Sparse Halfspaces with Constant Malicious Noise Rate
  14. NeurIPS 2026Benchmarks as Measurement Instruments: Quantifying Signal and Noise for More Efficient AI Evaluations Under Distribution Shift
  15. NeurIPS 2026Beyond Pairwise Supervision: Spectral Characteristic Matching for Data-Efficient Multimodal Alignment
  16. NeurIPS 2026Beyond the Half Approximation: Fair and Efficient Online Class Matching
  17. NeurIPS 2026Bidirectional Information Flow (BIF) - A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization
  18. NeurIPS 2026BiHashFormer: Hash-Driven Dual-Branch Transformer for Efficient Object Detection in HRW Shots
  19. NeurIPS 2026BLANP: Memory-Efficient Backpropagation-Free Local Training via Antithetic Node Perturbation
  20. NeurIPS 2026BROS: Bias-Corrected Randomized Subspaces for Memory-Efficient Single-Loop Bilevel Optimization
  21. NeurIPS 2026ByteDistill: Cross-Tokenizer Distillation via Chunk-wise Byte-Level Distribution Alignment
  22. NeurIPS 2026CELEUS: Certifiable and Efficient LLM Evaluation via E-Processes
  23. NeurIPS 2026CHoRD: Coordinating Scheduling and Data Placement for Efficient Deep Neural Network Inference on Chiplet-Based GPUs
  24. NeurIPS 2026Communication-Efficient LLM Adaptation over Decentralized GPU Meshes
  25. NeurIPS 2026Communication-Efficient Personalized Adaptation via Federated-Local Model Merging
  26. NeurIPS 2026CommunityKV: Efficient Long-Context Decoding via Graph Partitioning
  27. NeurIPS 2026CompactAttention: Accelerating Chunked Prefill with Block-Union KV Selection
  28. NeurIPS 2026Confidence-Based Decoding is Provably Efficient for Diffusion Language Models
  29. NeurIPS 2026Constrained Decoding for Diffusion Language Models via Efficient Inference over Finite Automata
  30. NeurIPS 2026CoPE-VideoLM: Leveraging Codec Primitives For Efficient Video Language Modelling
  31. NeurIPS 2026CRUMB: Efficient Prior Fitted Network Inference via Distributionally Matched Context Batching
  32. NeurIPS 2026Data-Constrained Language Model Pretraining: Improved Regularization and Scaling Laws
  33. NeurIPS 2026Data-Free Reservoir Features for Efficient Long-Horizon Cold-Start Continual Learning
  34. NeurIPS 2026Dataset Distillation via Drifting
  35. NeurIPS 2026Decomposing and Reshaping Scaling Laws through Token Learning Times
  36. NeurIPS 2026Depth through Recurrence: Towards Ultra-Efficient On-Device ASR
  37. NeurIPS 2026DrugSAGE: Self-evolving Agent Experience for Efficient State-of-the-Art Drug Discovery
  38. NeurIPS 2026DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts
  39. NeurIPS 2026Dynamic Convolutions Improve Transformers
  40. NeurIPS 2026Dynamic Resolution Routing for Efficient Egocentric Grounding
  41. NeurIPS 2026Dynamics-Aware Sparse Attention for Efficient Autoregressive Video Diffusion
  42. NeurIPS 2026DyRA: Dynamic Residual Approximation for Efficient Matrix Multiplication in DNNs
  43. NeurIPS 2026Efficient Algorithms for Distributed Saddle Problems
  44. NeurIPS 2026Efficient Algorithms For Fully Dynamic Bipartite Matching In Metric Spaces
  45. NeurIPS 2026Efficient algorithms for linear regression with heteroskedastic errors
  46. NeurIPS 2026Efficient Benchmarking Is Just Feature Selection and Multiple Regression
  47. NeurIPS 2026Efficient Brain-to-Speech Decoding with Fixed-Delay Spiking Neural Networks
  48. NeurIPS 2026Efficient Collaborative LLM Fine-Tuning over Heterogeneous Mobile Devices via Many Backbones to One Side-Network Tuning
  49. NeurIPS 2026Efficient Computation and Best-Response Dynamics in Anonymous Two-Action Games with Linear Utilities
  50. NeurIPS 2026Efficient Decoder Scaling Strategy for Constructive Neural Routing Solvers

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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