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 419 篇,第 3 / 9 页
- ICLR 2026Out of the Memory Barrier: A Highly Memory-Efficient Training System for LLMs with Million-Token Contexts
- ICLR 2026ParoQuant: Pairwise Rotation Quantization for Efficient Reasoning LLM Inference
- ICLR 2026PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery
- ICLR 2026PhaseFormer: From Patches to Phases for Efficient and Effective Time Series Forecasting
- ICLR 2026PiCa: Parameter-Efficient Fine-Tuning with Column Space Projection
- ICLR 2026Pre-training under infinite compute
- ICLR 2026ProxyAttn: Guided Sparse Attention via Representative Heads
- ICLR 2026QKV Projections Require a Fraction of Their Memory
- ICLR 2026Qronos: Correcting the Past by Shaping the Future... in Post-Training Quantization
- ICLR 2026Quantized Gradient Projection for Memory-Efficient Continual Learning
- ICLR 2026QuoKA: Query-Oriented KV Selection for Efficient LLM Prefill
- ICLR 2026RainPro-8: An Efficient Deep Learning Model to Estimate Rainfall Probabilities Over 8 Hours
- ICLR 2026Remaining-data-free Machine Unlearning by Suppressing Sample Contribution
- ICLR 2026Rethinking JEPA: Compute‑Efficient Video Self-Supervised Learning with Frozen Teachers
- ICLR 2026RMAAT: Astrocyte-Inspired Memory Compression and Replay for Efficient Long-Context Transformers
- ICLR 2026Scalable Random Wavelet Features: Efficient Non-Stationary Kernel Approximation with Convergence Guarantees
- ICLR 2026Scaling Laws Meet Model Architecture: Toward Inference-Efficient LLMs
- ICLR 2026Scaling Laws Revisited: Modeling the Role of Data Quality in Language Model Pretraining
- ICLR 2026Scaling Up, Speeding Up: A Benchmark of Speculative Decoding for Efficient LLM Test-Time Scaling
- ICLR 2026Scaling with Collapse: Efficient and Predictable Training of LLM Families
- ICLR 2026SecP-Tuning: Efficient Privacy-Preserving Prompt Tuning for Large Language Models via MPC
- ICLR 2026Sem-MoE: Semantic-aware Model-Data Collaborative Scheduling for Efficient MoE Inference
- ICLR 2026Semantic Voting: A Self-Evaluation-Free Approach for Efficient LLM Self-Improvement on Unverifiable Open-ended Tasks
- ICLR 2026SERE: Similarity-based Expert Re-routing for Efficient Batch Decoding in MoE Models
- ICLR 2026SparseEval: Efficient Evaluation of Large Language Models by Sparse Optimization
- ICLR 2026SPICE: Submodular Penalized Information–Conflict Selection for Efficient Large Language Model Training
- ICLR 2026SSDi8: Accurate and Efficient 8-bit Quantization for State Space Duality
- ICLR 2026STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization
- ICLR 2026Stopping Computation for Converged Tokens in Masked Diffusion-LM Decoding
- ICLR 2026Test-Time Efficient Pretrained Model Portfolios for Time Series Forecasting
- ICLR 2026TGM: A Modular and Efficient Library for Machine Learning on Temporal Graphs
- ICLR 2026TokenSeek: Memory Efficient Fine Tuning via Instance-Aware Token Ditching
- ICLR 2026Towards Greater Leverage: Scaling Laws for Efficient Mixture-of-Experts Language Models
- ICLR 2026Towards Lossless Memory-efficient Training of Spiking Neural Networks via Gradient Checkpointing and Spike Compression
- ICLR 2026ULD-Net: Enabling Ultra-Low-Degree Fully Polynomial Networks for Homomorphically Encrypted Inference
- ICLR 2026UltraMemV2: Memory Networks Scaling to 120B Parameters with Superior Long-Context Learning
- ICLR 2026UniCon: Unified Framework for Efficient Contrastive Alignment via Kernels
- ICLR 2026Unified and Efficient Multi-view Clustering from Probabilistic Perspective
- ICLR 2026Universal Model Routing for Efficient LLM Inference
- ICLR 2026Unlocking Full Efficiency of Token Filtering in Large Language Model Training
- ICLR 2026Unveiling Downstream Performance Scaling of LLMs: A Clustering-Based Perspective
- ICLR 2026VQ-Transplant: Efficient VQ-Module Integration for Pre-trained Visual Tokenizers
- ICLR 2026What Scales in Cross-Entropy Scaling Law?
- ICLR 2026Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs
- ICLR 2026WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference
- ICLR 2026xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
- ICLR 2026Your VAR Model is Secretly an Efficient and Explainable Generative Classifier
- ICLR 2026ZeroSiam: An Efficient Siamese for Test-Time Entropy Optimization without Collapse
- ICLR 2025(Mis)Fitting Scaling Laws: A Survey of Scaling Law Fitting Techniques in Deep Learning
- ICLR 2025$\text{D}_{2}\text{O}$: Dynamic Discriminative Operations for Efficient Long-Context Inference of Large Language Models
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。