分布式训练论文趋势 2023–2026
并行与大规模训练
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 396 篇被归入该主题的论文。
主要结论
- 分布式训练论文从 2023 年的 95 篇增长到 2026 年的 98 篇，三年间扩大到约 1.0 倍。
- NeurIPS 是发分布式训练论文最多的会议，2023–2026 年共 208 篇，占四个会议总量的 53%。
- 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 10 篇。
- 在「效率与系统」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的硬件协同是 4.4 倍，分布式训练是 1.0 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 54 | 10 | 28 | 3 | 95 |
| 2024 | 49 | 12 | 8 | 5 | 74 |
| 2025 | 69 | 18 | 40 | 2 | 129 |
| 2026 | 36 | 18 | 42 | 2 | 98 |
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 2026AgentWeave: Efficient Distributed Agent Serving via Flow Decomposition
- ICML 2026Breaking the Capacity Bottleneck in Model-Heterogeneous Federated Learning via Gradual Model Restoration
- ICLR 2026Cascadia: An Efficient Cascade Serving System for Large Language Models
- CVPR 2026Finding Distributed Object-Centric Properties in Self-Supervised Transformers
- NeurIPS 2025A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments
- ICML 2025BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
- ICLR 2025Addressing Label Shift in Distributed Learning via Entropy Regularization
- CVPR 2025Real-time High-fidelity Gaussian Human Avatars with Position-based Interpolation of Spatially Distributed MLPs
- NeurIPS 2024Communication Efficient Distributed Training with Distributed Lion
- ICML 2024Embarrassingly Parallel GFlowNets
- ICLR 2024Benchmarking Algorithms for Federated Domain Generalization
- CVPR 2024Deciphering 'What' and 'Where' Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations
- NeurIPS 20232Direction: Theoretically Faster Distributed Training with Bidirectional Communication Compression
- ICML 2023Block Subsampled Randomized Hadamard Transform for Nyström Approximation on Distributed Architectures
- ICLR 2023Distributed Extra-gradient with Optimal Complexity and Communication Guarantees
- CVPR 2023DisCo-CLIP: A Distributed Contrastive Loss for Memory Efficient CLIP Training
- NeurIPS 2026Do We Need Asynchronous SGD? On the Near-Optimality of Synchronous Methods
- ICML 2026Clipping Makes Distributed and Federated Asynchronous SGD Robust to Stragglers
- ICLR 2026DualMap: Enabling Both Cache Affinity and Load Balancing for Distributed LLM Serving
- CVPR 2026Parallel Rigidity Matters for Bundle Adjustment
全部分布式训练论文
共 208 篇，第 5 / 5 页
- NeurIPS 2023TMT-VIS: Taxonomy-aware Multi-dataset Joint Training for Video Instance Segmentation
- NeurIPS 2023Tools for Verifying Neural Models' Training Data
- NeurIPS 2023Towards Accelerated Model Training via Bayesian Data Selection
- NeurIPS 2023Training Transformers with 4-bit Integers
- NeurIPS 2023TRIAGE: Characterizing and auditing training data for improved regression
- NeurIPS 2023UE4-NeRF:Neural Radiance Field for Real-Time Rendering of Large-Scale Scene
- NeurIPS 2023Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
- NeurIPS 2023YouTube-ASL: A Large-Scale, Open-Domain American Sign Language-English Parallel Corpus
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 查分布式训练在 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": "distributed-training"}
常见问题
- 2023–2026 年四大会议一共有多少篇分布式训练论文？
- 共 396 篇，按年份分别是 2023 年 95 篇、2024 年 74 篇、2025 年 129 篇、2026 年 98 篇。
- NeurIPS 2026 有多少篇分布式训练论文？
- NeurIPS 2026 有 36 篇分布式训练论文，上一届是 69 篇。
- ICLR 2026 有多少篇分布式训练论文？
- ICLR 2026 有 18 篇分布式训练论文，上一届是 18 篇。
- ICML 2026 有多少篇分布式训练论文？
- ICML 2026 有 42 篇分布式训练论文，上一届是 40 篇。
- CVPR 2026 有多少篇分布式训练论文？
- CVPR 2026 有 2 篇分布式训练论文，上一届是 2 篇。
- 哪个会议的分布式训练论文最多？
- NeurIPS，2023–2026 年共 208 篇。