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 6 / 10 页
- NeurIPS 2025FADRM: Fast and Accurate Data Residual Matching for Dataset Distillation
- NeurIPS 2025Fair Minimum Labeling: Efficient Temporal Network Activations for Reachability and Equity
- NeurIPS 2025FastLongSpeech: Enhancing Large Speech-Language Models for Efficient Long-Speech Processing
- NeurIPS 2025FedRW: Efficient Privacy-Preserving Data Reweighting for Enhancing Federated Learning of Language Models
- NeurIPS 2025First Attentions Last: Better Exploiting First Attentions for Efficient Parallel Training
- NeurIPS 2025FlashBias: Fast Computation of Attention with Bias
- NeurIPS 2025FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts
- NeurIPS 2025FraPPE: Fast and Efficient Preference-Based Pure Exploration
- NeurIPS 2025Frequency-Aware Token Reduction for Efficient Vision Transformer
- NeurIPS 2025Functional Scaling Laws in Kernel Regression: Loss Dynamics and Learning Rate Schedules
- NeurIPS 2025GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
- NeurIPS 2025Gemstones: A Model Suite for Multi-Faceted Scaling Laws
- NeurIPS 2025Generalized Linear Bandits: Almost Optimal Regret with One-Pass Update
- NeurIPS 2025Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts
- NeurIPS 2025GMV: A Unified and Efficient Graph Multi-View Learning Framework
- NeurIPS 2025Gradient Multi-Normalization for Efficient LLM Training
- NeurIPS 2025Group-Level Data Selection for Efficient Pretraining
- NeurIPS 2025GSPN-2: Efficient Parallel Sequence Modeling
- NeurIPS 2025Hadamard Test is Sufficient for Efficient Quantum Gradient Estimation with Lie Algebraic Symmetries
- NeurIPS 2025Harmony in Divergence: Towards Fast, Accurate, and Memory-efficient Zeroth-order LLM Fine-tuning
- NeurIPS 2025Hierachical Balance Packing: Towards Efficient Supervised Fine-tuning for Long-Context LLM
- NeurIPS 2025HiFC: High-efficiency Flash-based KV Cache Swapping for Scaling LLM Inference
- NeurIPS 2025HollowFlow: Efficient Sample Likelihood Evaluation using Hollow Message Passing
- NeurIPS 2025Hybrid Re-matching for Continual Learning with Parameter-Efficient Tuning
- NeurIPS 2025HybridNorm: Towards Stable and Efficient Transformer Training via Hybrid Normalization
- NeurIPS 2025Hyperbolic Dataset Distillation
- NeurIPS 2025HyperET: Efficient Training in Hyperbolic Space for Multi-modal Large Language Models
- NeurIPS 2025Implicit-ARAP: Efficient Handle-Guided Neural Field Deformation via Local Patch Meshing
- NeurIPS 2025Improved Scaling Laws in Linear Regression via Data Reuse
- NeurIPS 2025Improving Decision Trees through the Lens of Parameterized Local Search
- NeurIPS 2025InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion
- NeurIPS 2025Interpretable and Parameter Efficient Graph Neural Additive Models with Random Fourier Features
- NeurIPS 2025Irrational Complex Rotations Empower Low-bit Optimizers
- NeurIPS 2025Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search
- NeurIPS 2025Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization
- NeurIPS 2025Layer as Puzzle Pieces: Compressing Large Language Models through Layer Concatenation
- NeurIPS 2025Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
- NeurIPS 2025LayerNavigator: Finding Promising Intervention Layers for Efficient Activation Steering in Large Language Models
- NeurIPS 2025Learned Prefix Caching for Efficient LLM Inference
- NeurIPS 2025Learning in Compact Spaces with Approximately Normalized Transformer
- NeurIPS 2025Learning quadratic neural networks in high dimensions: SGD dynamics and scaling laws
- NeurIPS 2025Less Is More, but Where? Dynamic Token Compression via LLM-Guided Keyframe Prior
- NeurIPS 2025Linear Attention for Efficient Bidirectional Sequence Modeling
- NeurIPS 2025LLM at Network Edge: A Layer-wise Efficient Federated Fine-tuning Approach
- NeurIPS 2025LookWhere? Efficient Visual Recognition by Learning Where to Look and What to See from Self-Supervision
- NeurIPS 2025LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
- NeurIPS 2025Mamba Modulation: On the Length Generalization of Mamba Models
- NeurIPS 2025Mamba Only Glances Once (MOGO): A Lightweight Framework for Efficient Video Action Detection
- NeurIPS 2025Memory-Efficient Training with In-Place FFT Implementation
- NeurIPS 2025Memory-Efficient Visual Autoregressive Modeling with Scale-Aware KV Cache Compression
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。