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
- 高效训练论文从 2023 年的 346 篇增长到 2026 年的 603 篇,三年间扩大到约 1.7 倍。
- NeurIPS 是发高效训练论文最多的会议,2023–2026 年共 499 篇,占四个会议总量的 28%。
- 交叉方向里涨得最快的是深度学习 · large language models:同时属于两个主题的论文从 2023 年的 6 篇增至 2026 年的 50 篇。
- 在「效率与系统」的 5 个主题里,它的 2026 年论文数排第 3;同组增长最快的硬件协同是 4.4 倍,高效训练是 1.7 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 112 | 67 | 83 | 84 | 346 |
| 2024 | 20 | 78 | 122 | 80 | 300 |
| 2025 | 190 | 126 | 118 | 82 | 516 |
| 2026 | 177 | 148 | 169 | 109 | 603 |
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 2026Adaptive Residual Quantization for Memory-Efficient Temporal Action Segmentation
- ICML 2026A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization
- ICLR 2026An Efficient SE(p)-Invariant Transport Metric Driven by Polar Transport Discrepancy-based Representation
- CVPR 2026A Bit is All You Need Efficient Video Capture via
- NeurIPS 20254DGCPro: Efficient Hierarchical 4D Gaussian Compression for Progressive Volumetric Video Streaming
- ICML 2025A Sample Efficient Conditional Independence Test in the Presence of Discretization
- ICLR 2025Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator
- CVPR 2025Accurate Scene Text Recognition with Efficient Model Scaling and Cloze Self-Distillation
- NeurIPS 2024$\texttt{dattri}$: A Library for Efficient Data Attribution
- ICML 2024A fast algorithm to simulate nonlinear resistive networks
- ICLR 2024Dictionary Contrastive Learning for Efficient Local Supervision without Auxiliary Networks
- CVPR 2024Deep-TROJ: An Inference Stage Trojan Insertion Algorithm through Efficient Weight Replacement Attack
- NeurIPS 2023Alternating Updates for Efficient Transformers
- ICML 2023Auxiliary Modality Learning with Generalized Curriculum Distillation
- ICLR 2023A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
- CVPR 2023A Rotation-Translation-Decoupled Solution for Robust and Efficient Visual-Inertial Initialization
- NeurIPS 2026Advanced Routing as Regularization Allocation for Efficient Diffusion Transformer Training
- ICML 2026Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance
- ICLR 2026AQER: A Scalable and Efficient Data Loader for Digital Quantum Computers
- CVPR 2026Adaptive Bayesian Early-Exit Networks for Efficient Non-Transferable Learning
全部高效训练论文
共 492 篇,第 6 / 10 页
- ICML 2025Predictive Data Selection: The Data That Predicts Is the Data That Teaches
- ICML 2025Primphormer: Efficient Graph Transformers with Primal Representations
- ICML 2025ProofAug: Efficient Neural Theorem Proving via Fine-grained Proof Structure Analysis
- ICML 2025QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration
- ICML 2025Reliable and Efficient Amortized Model-based Evaluation
- ICML 2025Residual Matrix Transformers: Scaling the Size of the Residual Stream
- ICML 2025Reward-Guided Speculative Decoding for Efficient LLM Reasoning
- ICML 2025Robust Consensus Anchor Learning for Efficient Multi-view Subspace Clustering
- ICML 2025RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
- ICML 2025SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-thread INT4 Quantization
- ICML 2025Sample Efficient Demonstration Selection for In-Context Learning
- ICML 2025Scalable Model Merging with Progressive Layer-wise Distillation
- ICML 2025Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks
- ICML 2025Scaling Inference-Efficient Language Models
- ICML 2025Scaling Laws for Floating–Point Quantization Training
- ICML 2025Scaling Probabilistic Circuits via Monarch Matrices
- ICML 2025SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
- ICML 2025SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization
- ICML 2025Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
- ICML 2025Sparse Spectral Training and Inference on Euclidean and Hyperbolic Neural Networks
- ICML 2025SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity
- ICML 2025SpikF: Spiking Fourier Network for Efficient Long-term Prediction
- ICML 2025Star Attention: Efficient LLM Inference over Long Sequences
- ICML 2025SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training
- ICML 2025TabFlex: Scaling Tabular Learning to Millions with Linear Attention
- ICML 2025Temporal Query Network for Efficient Multivariate Time Series Forecasting
- ICML 2025Tensor Decomposition Based Memory-Efficient Incremental Learning
- ICML 2025The Hidden Joules: Evaluating the Energy Consumption of Vision Backbones for Progress Towards More Efficient Model Inference
- ICML 2025The Limits of Tractable Marginalization
- ICML 2025The Panaceas for Improving Low-Rank Decomposition in Communication-Efficient Federated Learning
- ICML 2025TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting
- ICML 2025TimePro: Efficient Multivariate Long-term Time Series Forecasting with Variable- and Time-Aware Hyper-state
- ICML 2025Training Deep Learning Models with Norm-Constrained LMOs
- ICML 2025UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model
- ICML 2025Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
- ICML 2025XAttention: Block Sparse Attention with Antidiagonal Scoring
- ICML 2025xLSTM 7B: A Recurrent LLM for Fast and Efficient Inference
- ICML 2024A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design
- ICML 2024A Dynamical Model of Neural Scaling Laws
- ICML 2024A fast algorithm to simulate nonlinear resistive networks
- ICML 2024A New Computationally Efficient Algorithm to solve Feature Selection for Functional Data Classification in High-dimensional Spaces
- ICML 2024A Tale of Tails: Model Collapse as a Change of Scaling Laws
- ICML 2024AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning
- ICML 2024An Efficient Maximal Ancestral Graph Listing Algorithm
- ICML 2024An Efficient Self-Learning Framework For Interactive Spoken Dialog Systems
- ICML 2024APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
- ICML 2024Asymptotically Optimal and Computationally Efficient Average Treatment Effect Estimation in A/B testing
- ICML 2024Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
- ICML 2024Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
- ICML 2024CaM: Cache Merging for Memory-efficient LLMs Inference
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"}
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。