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 4 / 5 页
- ICML 2026VBA: Vector Bundle Attention for Intrinsically Geometric Representation Learning
- ICML 2026Vector Linking via Cross-Model Local Isometric Consistency
- ICML 2026View Space: Learning Representation across Arbitrary Graphs
- ICML 2026What Makes a Representation Good for Single-Cell Perturbation Prediction?
- ICML 2026When Distance Distracts: Representation Distance Bias in BT-Loss for Reward Models
- NeurIPS 2026A Unified Uncertainty Representation for Graph Neural Networks via Doubly-Spectral Stochastic Expansion
- NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
- NeurIPS 2026Anchor3DGS: Feed-Forward 3D Gaussian Splatting with Compact Anchor-Based Representation
- NeurIPS 2026AnchorRep: Defending LLMs Against Cross-Model Adversarial Transfer via Representation Repulsion
- NeurIPS 2026Approximation in Contrastive Representation Learning
- NeurIPS 2026Biological Graph Priors Enable Representation Learning for Cellular Microscopy
- NeurIPS 2026Boosting Graph Contrastive Learning via Manifold-Guided Representation Disentanglement
- NeurIPS 2026Class–Domain Discriminability Guided Representation Enhancement for Domain Generalization
- NeurIPS 2026Closed-Form Implicit Neural Representations
- NeurIPS 2026Contrastive Representation Shaping for LLM Unlearning
- NeurIPS 2026CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers
- NeurIPS 2026Deadline-Constrained Dynamic Workflow Scheduling Can be Cast as a Representation Learning Problem
- NeurIPS 2026Decentralized Coupled Representation Learning
- NeurIPS 2026DiffRisk: Diffusion Representation Learning with Informative Missingness for Health Risk Prediction
- NeurIPS 2026Disentangled Representation Learning via Flow Matching
- NeurIPS 2026dRAE: Representation Autoencoder with Hyper-Spherical Codes
- NeurIPS 2026Dynamic Representation Modeling for Federated Medical Image Domain Generalization
- NeurIPS 2026Energy-Adaptive Equivariant State Space Models for Noise-Robust Protein Structure Representation
- NeurIPS 2026Escaping Parameter Space: Tight Generalization Bounds via Representation Quality
- NeurIPS 2026Finding Koopman Invariant Subspaces via Personalized PageRank
- NeurIPS 2026FuncFormer: Circuit Representation Learning via the Flow of Functional Propagation
- NeurIPS 2026GaitLingo: Self-Supervised Gait Representation Learning with Language Priors
- NeurIPS 2026GEM: A Dual-Scale Architecture for Graph-Level Hierarchical Representation Learning
- NeurIPS 2026Geometry-Aware Self-Supervised Electrophysiology Representation Learning
- NeurIPS 2026GIFT: Representation Geometry Matters for Single-Domain Generalized Object Detection
- NeurIPS 2026Hadamard Representation: Scaffolding Performance Across Model-free RL
- NeurIPS 2026Harder the Task, Sparser the Representation: Sparsity as a Learning Signature of Capability in LLMs
- NeurIPS 2026Hierarchical Graph Representation Learning with Pooling-Induced Substructures
- NeurIPS 2026HiLoc: A Hierarchical Representation Method for Spatial Localization in Multimodal Large Language Models
- NeurIPS 2026How Do Language Models Compose Functions?
- NeurIPS 2026Hypergraph Representation Learning with Hyperlink Random Effects
- NeurIPS 2026Intrinsic Information Theoretic Analysis of ReLU Nets
- NeurIPS 2026Is a Linear Probe Evidence of a Linear Representation?
- NeurIPS 2026KINDER: Kernel-based Independence for Fair Representation Learning via Prototype-space Erasure
- NeurIPS 2026Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis
- NeurIPS 2026LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift
- NeurIPS 2026MCM-DM: Towards Better Spatio-Temporal Event Representation Learning via Discrete Morse Theory
- NeurIPS 2026Mind the Heads: Topological Representation Alignment for Multimodal LLMs
- NeurIPS 2026MinSteer: Minimal-Pair Steering via Two-Stage Cached Continuation
- NeurIPS 2026MIRAGE: Duality-Inspired MILP Augmentation for Representation Learning
- NeurIPS 2026MoRe: Modular Representations for Principled Continual Representation Learning on Sequential Data
- NeurIPS 2026Neural-Behavioral Representation of Natural Whole-body Movement in Monkeys
- NeurIPS 2026NIKA: Efficient Neural Video Representation via Structured Latent Diversity
- NeurIPS 2026NOCE-Net: Representation Learning for Battery Operational Context via Nested Sequence Modelling
- NeurIPS 2026One Unified Representation: Resolving the Appearance-Semantics Dilemma via Structural Regularization
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