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