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 603 篇，第 12 / 13 页

551. NeurIPS 2026Proper Agnostic Learning of Functions of Halfspaces
552. NeurIPS 2026QueryStop: Dynamic Stop Signals for Efficient Streaming Inference
553. NeurIPS 2026Random Attention Pattern Learning Enables Emergent Capabilities
554. NeurIPS 2026Relaxed On-Policy Distillation: Selective Credit Allocation for Scaling Reasoning Efficiently
555. NeurIPS 2026RelFlexformer: Efficient Attention Transformers for Integrable Relative Positional Encodings
556. NeurIPS 2026RePiD: Efficient Recursive Pixel-Space Diffusion via Hierarchical Patch Denoising
557. NeurIPS 2026Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets?
558. NeurIPS 2026Rethinking Expressivity and Efficiency in Test-Time Training
559. NeurIPS 2026Rethinking Infrared Small Target Detection: A Foundation Driven Efficient Paradigm
560. NeurIPS 2026Rich Insights from Cheap Signals: Efficient Evaluations via Tensor Factorization
561. NeurIPS 2026Robust and Efficient Backdoor Mitigation for ML Models via Tolerant Property Testing
562. NeurIPS 2026Robust and Efficient Continual Model Merging via Global Singular Subspace Separation and Restoration
563. NeurIPS 2026ROCKET: Rapid Optimization via Calibration-guided Knapsack-Enhanced Truncation for Efficient Model Compression
564. NeurIPS 2026RubiConv - Efficient Boundary-Respecting Convolutions
565. NeurIPS 2026SageSched: Efficient LLM Scheduling Confronting Demand Uncertainty and Hybridity
566. NeurIPS 2026Sample-Efficient Optimization over Generative Priors via Coarse Learnability
567. NeurIPS 2026Scaling Laws for SAE Training Data
568. NeurIPS 2026Sharp feature-learning transitions and Bayes-optimal neural scaling laws in extensive-width networks
569. NeurIPS 2026Should We Pay This Much for Robustness? Efficient Proxy Certificates with Marginal Guarantees
570. NeurIPS 2026Show Me What You Don’t Know: Efficient Sampling from Invariant Sets for Model Validation
571. NeurIPS 2026SHRED: Retain-Set-Free Unlearning via Self-Distillation with Logit Demotion
572. NeurIPS 2026SimpleEvol: Efficient Intelligence Conversion via Less Human Prior in Automated Heuristic Design
573. NeurIPS 2026SnapMLA: Efficient Long-Context MLA Decoding via Hardware-Aware FP8 Quantized Pipelining
574. NeurIPS 2026SparDA: Sparse Decoupled Attention for Efficient Long-Context LLM Inference
575. NeurIPS 2026Sparse Attention as a Range Searching Problem: Towards an Inference-Efficient Index for KV Cache
576. NeurIPS 2026Speculative Self-Distillation enables Efficient Knowledge Internalization
577. NeurIPS 2026Speed Predictions for Online Energy-Efficient Scheduling
578. NeurIPS 2026Spike-SFT: Selective Parameter Enhancement and Fusion for Efficient Spiking Neural Networks
579. NeurIPS 2026Step-dLLM: Adaptive Step-aware Sparse Attention for Efficient Diffusion LLM Inference
580. NeurIPS 2026Stroke-Audited Quadratic Bezier Splatting with Structural Initialization for Efficient Painting Rendering
581. NeurIPS 2026Structured Unitary Tensor Network Representations for Circuit-Efficient Quantum Data Encoding
582. NeurIPS 2026Subdata Selection: A Unified Framework for Optimal Selection and Statistical Efficiency Assessment
583. NeurIPS 2026SWE-Crafter: Scaling Executable Multilingual Software Engineering Data with Meta-Skill Agents
584. NeurIPS 2026Systematic Scaling Analysis of Jailbreak Attacks in Large Language Models
585. NeurIPS 2026Talk Less, Work More: Communication-Efficient Decentralized Stochastic Approximation
586. NeurIPS 2026Target-Budget Best-Function Identification for Scaling-Law-Guided Model Selection
587. NeurIPS 2026TeMPO: Frame-Causal Token Compression for Efficient Video Large Language Model
588. NeurIPS 2026Temporal Smoothness Constraints on Efficient Neurobiological Codes Imply Temporal Specialization
589. NeurIPS 2026The Dormant Spiking Neuron: A State-Driven Mechanism for Efficient Spiking Neural Networks
590. NeurIPS 2026The Kernel Reality Check: Benchmarking and Distilling Efficient Attention at Scale
591. NeurIPS 2026The SEC Filings Dataset: Reconstructing U.S. Corporate and Financial Disclosures into Layout-Faithful and Token-Efficient Pretraining Data
592. NeurIPS 2026Token Filtering: Online Attention Pruning via KV Similarity for Efficient LLM Inference
593. NeurIPS 2026TokenRouter: Efficient Serving System for Token-Level LLM Routing
594. NeurIPS 2026ToLD: Efficient Time Series Forecasting via Tokenized Truncated Latent Diffusion
595. NeurIPS 2026Towards Principled Efficient Rollout Allocation in Test-Time Training
596. NeurIPS 2026TTB: Test-time MLP Baking for Efficient Rendering of Decoder-only View Synthesis Models
597. NeurIPS 2026Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting
598. NeurIPS 2026UTOPI: Efficient Egocentric Long-Video Understanding in AR via User-Guided Token Pre-Compression
599. NeurIPS 2026Vendi Anomaly Scores for Efficient and Accurate Anomaly Detection
600. NeurIPS 2026Vortex: Efficient and Programmable Sparse Attention Serving

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。