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 499 篇,第 2 / 10 页
- NeurIPS 2026Efficient Fine-Tuning for Structured Sparsity Under Group Repartitioning
- NeurIPS 2026Efficient Image Synthesis with Sphere Latent Encoder
- NeurIPS 2026Efficient Label Distribution Inference Attack and Defense on Classifier Weights in Federated Learning
- NeurIPS 2026Efficient Learning of Truncated Boolean Product Distributions: Influence to the Rescue
- NeurIPS 2026Efficient LLM Adaptation with Forward-Only Passes
- NeurIPS 2026Efficient Memory Crystallization for Graph Learning under Non-Stationary Distribution Shifts
- NeurIPS 2026Efficient Pre-Training with Token Superposition
- NeurIPS 2026Efficient Scaling of LLM Training with Flexible Context Parallelism
- NeurIPS 2026Efficient Serving for Dynamic Agent Workflows with Prediction-based KV-Cache Management
- NeurIPS 2026Efficient Training of Deep Spiking Neural Networks with Input-Driven Derivative-Free Updates
- NeurIPS 2026Efficient Variational Inference for Log-Gaussian Cox Processes via Voronoi Tessellation
- NeurIPS 2026Efficient, Accurate and Stable Gradients for Neural ODEs
- NeurIPS 2026Efficiently Aligning Draft Models via Parameter- and Data-Efficient Adaptation
- NeurIPS 2026EngramState: Loadable Tool Priors for Efficient Function Calling
- NeurIPS 2026EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning
- NeurIPS 2026Fast KVzip: Efficient and Accurate LLM Inference with Gated KV Eviction
- NeurIPS 2026FELPS: Fair and Efficient Scheduling for Multi-LoRA Serving System
- NeurIPS 2026Finite-Memory Control of POMDPs: Fundamental Limits and Efficient Design
- NeurIPS 2026Finite-Sample and Communication-Efficient Networked Information Aggregation
- NeurIPS 2026Flash-KMeans: Fast and Memory-Efficient Exact K-Means
- NeurIPS 2026FlashMask-3: Efficient and Expressive Mask-Aware Distributed Attention
- NeurIPS 2026Flow-Direct: Feedback-Efficient and Reusable Guidance for Flow Models via Non-Parametric Guidance Field
- NeurIPS 2026From Experts to Sub-experts: Fine-grained Parameter-Efficient Fine-Tuning for MoE LLMs
- NeurIPS 2026Generative Cross-Entropy: A Strictly Proper Loss for Data-Efficient Classification
- NeurIPS 2026GramStatTexNet: Efficient, Interpretable, and Neuro-Inspired Texture Analysis-by-Synthesis
- NeurIPS 2026HetCCL: Efficient LLM Training on Heterogeneous Vendor GPUs
- NeurIPS 2026HiFloat4 Format for Language Model Pre-training on Ascend NPUs
- NeurIPS 2026Holistic Scaling Laws for Optimal Mixture-of-Experts Architecture Optimization
- NeurIPS 2026How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models
- NeurIPS 2026Human-Inspired, Task-Dimension-Guided Exploration for Efficient Learning and Transfer in High Dimensions
- NeurIPS 2026Hyperbolic Language Models: From Zipf to Compute-Optimal Scaling
- NeurIPS 2026HyperVAttention: Efficient Sparse Attention with Spatio-Temporal Clustering for Video Diffusion
- NeurIPS 2026IncAgg: Efficient Memory-Enhanced Graph Learning via Incremental Aggregation
- NeurIPS 2026Joint Sequence--Vocabulary Selection for Efficient LLM Distillation
- NeurIPS 2026Label-Efficient Dataset Pruning via Semi-Supervised Pseudo-Labeling
- NeurIPS 2026Learning to Foresee: Unveiling the Unlocking Efficiency of On-Policy Distillation
- NeurIPS 2026Leech Lattice Vector Quantization for Efficient LLM Compression
- NeurIPS 2026LEMON-ZEST: Evolution-Informed Tokenization for Efficient Protein Language Modeling
- NeurIPS 2026LIME: Link-based User-item Interaction Modeling with Decoupled XOR Attention for Efficient Test Time Scaling
- NeurIPS 2026LLM Routing Through the Lens of Recommendation: A Roadmap for Efficient AI Orchestration
- NeurIPS 2026Logical Distillation of Transformer Encoders
- NeurIPS 2026LoopPrune: Evolutionary Module Selection with Iterative Execution for Efficient Large Language Model Compression
- NeurIPS 2026Magnitude-preserving Layers Enable Efficient GANs
- NeurIPS 2026Map-Guided Caching: A Global Perspective for Efficient Diffusion Transformer
- NeurIPS 2026Matched-Control Tests of Partition-Source Claims in One Routed Distillation Family
- NeurIPS 2026MemForest: Efficient Agent Memory Management via EventTree Partitioning and Progressive Merging
- NeurIPS 2026Meta-memorization and memorization scaling laws in transformers
- NeurIPS 2026MGMem: An Efficient, Deterministic, and Provenance-Preserving Framework for Long-Horizon Agent Memory
- NeurIPS 2026Mixture-of-Top-$k$ Attention: Efficient Attention as Scalable Fast Weights
- NeurIPS 2026MoE-SpAc: Efficient MoE Inference Based on Speculative Activation Utility in Heterogeneous Edge Scenario
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。