深度学习 · representation learning论文趋势 2023–2026
ICML/NeurIPS 深度学习方向：representation_learning
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 802 篇被归入该主题的论文。
主要结论
- 深度学习 · representation learning论文从 2023 年的 259 篇降到 2026 年的 214 篇，热度在回落。
- NeurIPS 是发深度学习 · representation learning论文最多的会议，2023–2026 年共 279 篇，占四个会议总量的 35%。
- 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 11 篇增至 2026 年的 28 篇。
- 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 7；同组增长最快的扩散模型是 4.1 倍，深度学习 · representation learning是 0.8 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 | 58 | 31 | 58 | 259 |
| 2024 | 54 | 38 | 42 | 43 | 177 |
| 2025 | 54 | 37 | 35 | 26 | 152 |
| 2026 | 59 | 39 | 74 | 42 | 214 |
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 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
- ICML 2026Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
- ICLR 2026Boosting Open Set Recognition Performance through Modulated Representation Learning
- CVPR 2026CanonCGT Reference-Based Color Grading via Canonical Pivot Representation
- NeurIPS 2025Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
- ICML 2025Banyan: Improved Representation Learning with Explicit Structure
- ICLR 2025Edge-aware Image Smoothing with Relative Wavelet Domain Representation
- CVPR 20253D-SLNR: A Super Lightweight Neural Representation for Large-scale 3D Mapping
- NeurIPS 2024GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
- ICML 2024Data-free Neural Representation Compression with Riemannian Neural Dynamics
- ICLR 2024$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
- CVPR 2024Disentangled Prompt Representation for Domain Generalization
- NeurIPS 2023[Re] CrossWalk: Fairness-enhanced Node Representation Learning
- ICML 2023A theory of representation learning gives a deep generalisation of kernel methods
- ICLR 2023Bispectral Neural Networks
- CVPR 2023AnyFlow: Arbitrary Scale Optical Flow With Implicit Neural Representation
- NeurIPS 2026Approximation in Contrastive Representation Learning
- ICML 2026Amortized Maximum Inner Product Search with Learned Support Functions
- ICLR 2026Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement
- CVPR 2026Enhancing Visual Representation with Textual Semantics Textual Semantics-Powered Prototypes for
全部深度学习 · representation learning论文
共 214 篇，第 5 / 5 页
- NeurIPS 2026Oversmoothing as Representation Degeneracy in Neural Sheaf Diffusion
- NeurIPS 2026Predictive Representation Learning for Partially Observed Neural Dynamics
- NeurIPS 2026Primal-Dual Representation Learning for Low-Rank Constrained MDPs
- NeurIPS 2026Provably Efficient Representation Learning for Low-Rank CMDPs
- NeurIPS 2026Representation Forcing for Bottleneck-Free Unified Multimodal Models
- NeurIPS 2026Representation Learning Enables Scalable Multitask Deep Reinforcement Learning
- NeurIPS 2026Representation Preconditioning for Efficient Diffusion Model Training
- NeurIPS 2026Self-Distillation of Hidden Layers for Masked Self-Supervised Representation Learning
- NeurIPS 2026Senses Wide Shut: A Representation-Action Gap in Omnimodal LLMs
- NeurIPS 2026The Bayesian Origin of the Probability Weighting Function in Human Representation of Probabilities
- NeurIPS 2026The Geometry of Agent Skills: Non-Commutative Composition in Representation Space
- NeurIPS 2026TopoPrune: Robust Data Pruning via Unified Latent Space Topology
- NeurIPS 2026TRL-Bench: Standardizing Cross-Paradigm Representation-Level Evaluation of Tabular Encoders
- NeurIPS 2026What Does the Brain See? Multiview Neural Representation to Demystify the Brain-Visual Alignment
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 查深度学习 · representation learning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": "dl-representation-learning"}
常见问题
- 2023–2026 年四大会议一共有多少篇深度学习 · representation learning论文？
- 共 802 篇，按年份分别是 2023 年 259 篇、2024 年 177 篇、2025 年 152 篇、2026 年 214 篇。
- NeurIPS 2026 有多少篇深度学习 · representation learning论文？
- NeurIPS 2026 有 59 篇深度学习 · representation learning论文，上一届是 54 篇。
- ICLR 2026 有多少篇深度学习 · representation learning论文？
- ICLR 2026 有 39 篇深度学习 · representation learning论文，上一届是 37 篇。
- ICML 2026 有多少篇深度学习 · representation learning论文？
- ICML 2026 有 74 篇深度学习 · representation learning论文，上一届是 35 篇。
- CVPR 2026 有多少篇深度学习 · representation learning论文？
- CVPR 2026 有 42 篇深度学习 · representation learning论文，上一届是 26 篇。
- 哪个会议的深度学习 · representation learning论文最多？
- NeurIPS，2023–2026 年共 279 篇。
「深度学习」下的其他主题
- 扩散模型 6,900
- 深度学习 · generative models and autoencoders 4,314
- 深度学习 · large language models 2,334
- 深度学习 · self supervised learning 1,958
- 深度学习 · graph neural networks 1,648
- 深度学习 · optimization 953
- 深度学习 · probabilistic methods 637
- 深度学习 · foundation models 536
- 深度学习 · causal inference 316
- 深度学习 · transfer learning 197