高效训练论文趋势 2023–2026

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。

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 8 / 10 页

351. ICML 2024InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models
352. ICML 2024Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization
353. ICML 2024Knowledge Distillation with Auxiliary Variable
354. ICML 2024Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs
355. ICML 2024Learning-Efficient Yet Generalizable Collaborative Filtering for Item Recommendation
356. ICML 2024Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
357. ICML 2024Measuring Stochastic Data Complexity with Boltzmann Influence Functions
358. ICML 2024Memory Efficient Neural Processes via Constant Memory Attention Block
359. ICML 2024MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization
360. ICML 2024Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
361. ICML 2024Navigating Scaling Laws: Compute Optimality in Adaptive Model Training
362. ICML 2024Nonparametric Teaching of Implicit Neural Representations
363. ICML 2024On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis
364. ICML 2024Online Cascade Learning for Efficient Inference over Streams
365. ICML 2024Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
366. ICML 2024Outlier-Efficient Hopfield Layers for Large Transformer-Based Models
367. ICML 2024Outlier-robust Kalman Filtering through Generalised Bayes
368. ICML 2024Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
369. ICML 2024Parameter-Efficient Fine-Tuning with Controls
370. ICML 2024Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
371. ICML 2024Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
372. ICML 2024Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
373. ICML 2024Quality-Diversity with Limited Resources
374. ICML 2024QUEST: Query-Aware Sparsity for Efficient Long-Context LLM Inference
375. ICML 2024Random Masking Finds Winning Tickets for Parameter Efficient Fine-tuning
376. ICML 2024Ranking-based Client Imitation Selection for Efficient Federated Learning
377. ICML 2024Replicable Learning of Large-Margin Halfspaces
378. ICML 2024REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updates
379. ICML 2024Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
380. ICML 2024Robust Yet Efficient Conformal Prediction Sets
381. ICML 2024Saliency strikes back: How filtering out high frequencies improves white-box explanations
382. ICML 2024Scalable AI Safety via Doubly-Efficient Debate
383. ICML 2024Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
384. ICML 2024Scaling Beyond the GPU Memory Limit for Large Mixture-of-Experts Model Training
385. ICML 2024Scaling Down Deep Learning with MNIST-1D
386. ICML 2024Scaling Laws for Fine-Grained Mixture of Experts
387. ICML 2024Scaling Laws for the Value of Individual Data Points in Machine Learning
388. ICML 2024See More Details: Efficient Image Super-Resolution by Experts Mining
389. ICML 2024Selecting Large Language Model to Fine-tune via Rectified Scaling Law
390. ICML 2024SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching
391. ICML 2024Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences
392. ICML 2024Simple linear attention language models balance the recall-throughput tradeoff
393. ICML 2024SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
394. ICML 2024SparQ Attention: Bandwidth-Efficient LLM Inference
395. ICML 2024Split-Ensemble: Efficient OOD-aware Ensemble via Task and Model Splitting
396. ICML 2024SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
397. ICML 2024Structured Inverse-Free Natural Gradient Descent: Memory-Efficient & Numerically-Stable KFAC
398. ICML 2024Tandem Transformers for Inference Efficient LLMs
399. ICML 2024Towards efficient deep spiking neural networks construction with spiking activity based pruning
400. ICML 2024Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration

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。