深度学习 · generative models and autoencoders论文趋势 2023–2026
ICML/NeurIPS 深度学习方向：generative_models_and_autoencoders
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 4,314 篇被归入该主题的论文。
主要结论
- 深度学习 · generative models and autoencoders论文从 2023 年的 1,216 篇增长到 2026 年的 1,430 篇，三年间扩大到约 1.2 倍。
- NeurIPS 是发深度学习 · generative models and autoencoders论文最多的会议，2023–2026 年共 1,714 篇，占四个会议总量的 40%。
- 交叉方向里涨得最快的是图像生成：同时属于两个主题的论文从 2023 年的 35 篇增至 2026 年的 150 篇。
- 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 2；同组增长最快的扩散模型是 4.1 倍，深度学习 · generative models and autoencoders是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 776 | 78 | 286 | 76 | 1,216 |
| 2024 | 349 | 174 | 139 | 106 | 768 |
| 2025 | 240 | 275 | 275 | 110 | 900 |
| 2026 | 349 | 303 | 604 | 174 | 1,430 |
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 2026A Critical $\beta$-Scale for Posterior Collapse in Dirichlet $\beta$-VAEs
- ICML 2026(1D) Ordered Tokens Enable Efficient Test-Time Search
- ICLR 2026``Noisier'’ Noise Contrastive Estimation is (Almost) Maximum Likelihood
- CVPR 2026Anchoring and Rescaling Attention for Semantically Coherent Inbetweening
- NeurIPS 2025Agnostic Learning under Targeted Poisoning: Optimal Rates and the Role of Randomness
- ICML 2025A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
- ICLR 2025A Watermark for Order-Agnostic Language Models
- CVPR 2025DUNE: Distilling a Universal Encoder from Heterogeneous 2D and 3D Teachers
- NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
- ICML 2024A Fixed-Point Approach for Causal Generative Modeling
- ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
- CVPR 2024Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
- NeurIPS 2023(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
- ICML 2023A Kernelized Stein Discrepancy for Biological Sequences
- ICLR 2023Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing
- CVPR 20233D GAN Inversion With Facial Symmetry Prior
- NeurIPS 2026Action-On-Item Preference Flow: A Shared Event Schema for Predictive and Generative Personalization
- ICML 2026$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
- ICLR 2026Analyzing and Evaluating Unbiased Language Model Watermark
- CVPR 2026Bidirectional Normalizing Flow From Data to Noise and Back
全部深度学习 · generative models and autoencoders论文
共 1,430 篇，第 5 / 29 页
- ICLR 2026Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis
- ICLR 2026Beyond Ensembles: Simulating All-Atom Protein Dynamics in a Learned Latent Space
- ICLR 2026Beyond Scattered Acceptance: Fast and Coherent Inference for DLMs via Longest Stable Prefixes
- ICLR 2026Bi-Lipschitz Autoencoder With Injectivity Guarantee
- ICLR 2026Bidirectional Predictive Coding
- ICLR 2026BioTamperNet: Affinity-Guided State-Space Model Detecting Tampered Biomedical Images
- ICLR 2026BranchGRPO: Stable and Efficient GRPO with Structured Branching in Diffusion Models
- ICLR 2026Break the Trade-off Between Watermark Strength and Speculative Sampling Efficiency for Language Models
- ICLR 2026Bridging Generalization Gap of Heterogeneous Federated Clients Using Generative Models
- ICLR 2026Bridging ML and algorithms: comparison of hyperbolic embeddings
- ICLR 2026CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention
- ICLR 2026Carré du champ flow matching: better quality-generalisation tradeoff in generative models
- ICLR 2026Characterizing Deep Research: A Benchmark and Formal Definition
- ICLR 2026Choices Speak Louder than Questions
- ICLR 2026CMT: Mid-Training for Efficient Learning of Consistency, Mean Flow, and Flow-Map Models
- ICLR 2026CO3: CONTRASTING CONCEPTS COMPOSE BETTER
- ICLR 2026Conditionally Whitened Generative Models for Probabilistic Time Series Forecasting
- ICLR 2026ConfHit: Conformal Generative Design via Nested Testing
- ICLR 2026Confident and Adaptive Generative Speech Recognition via Conformal Risk Control
- ICLR 2026Contact Wasserstein Geodesics for Non-Conservative Schrödinger Bridges
- ICLR 2026Continual Low-Rank Adapters for LLM-based Generative Recommender Systems
- ICLR 2026DecompGAIL: Learning Realistic Traffic Behaviors with Decomposed Multi-Agent Generative Adversarial Imitation Learning
- ICLR 2026Decoupled DMD: CFG Augmentation as the Spear, Distribution Matching as the Shield
- ICLR 2026Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling
- ICLR 2026DeepTRACE: Auditing Deep Research AI Systems for Tracking Reliability Across Citations and Evidence
- ICLR 2026DeepWeightFlow: Re-Basined Flow Matching for Generating Neural Network Weights
- ICLR 2026Delay Flow Matching
- ICLR 2026DeMo: Decoupled Momentum Optimization
- ICLR 2026Detecting and Mitigating Memorization in Diffusion Models through Anisotropy of the Log-Probability
- ICLR 2026Diagnosing and Improving Diffusion Models by Estimating Optimal Loss Value
- ICLR 2026DiCache: Let Diffusion Model Determine Its Own Cache
- ICLR 2026DiffSDA: Unsupervised Diffusion Sequential Disentanglement Across Modalities
- ICLR 2026Diffusion & Adversarial Schrödinger Bridges via Iterative Proportional Markovian Fitting
- ICLR 2026Diffusion Language Model Knows the Answer Before It Decodes
- ICLR 2026Diffusion Transformers with Representation Autoencoders
- ICLR 2026Discovering and Steering Interpretable Concepts in Large Generative Music Models
- ICLR 2026Disentanglement of Variations with Multimodal Generative Modeling
- ICLR 2026Distributionally Robust Optimization via Generative Ambiguity Modeling
- ICLR 2026Diversity-Aware Online Prompt Assignment to Generative Models
- ICLR 2026Do Not Let Low-Probability Tokens Over-Dominate in RL for LLMs
- ICLR 2026Does Higher Interpretability Imply Better Utility? A Pairwise Analysis on Sparse Autoencoders
- ICLR 2026DoFlow: Flow-based Generative Models for Interventional and Counterfactual Forecasting on Time Series
- ICLR 2026dParallel: Learnable Parallel Decoding for dLLMs
- ICLR 2026Dual-Solver: A Generalized ODE Solver for Diffusion Models with Dual Prediction
- ICLR 2026DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies
- ICLR 2026EchoMotion: Unified Human Video and Motion Generation via Dual-Modality Diffusion Transformer
- ICLR 2026EgoTwin: Dreaming Body and View in First Person
- ICLR 2026Eliminating VAE for Fast and High-Resolution Generative Detail Restoration
- ICLR 2026Energy-Based Transformers are Scalable Learners and Thinkers
- ICLR 2026Enhanced Generative Model Evaluation with Clipped Density and Coverage
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 · generative models and autoencoders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-generative-models-and-autoencoders"}
常见问题
- 2023–2026 年四大会议一共有多少篇深度学习 · generative models and autoencoders论文？
- 共 4,314 篇，按年份分别是 2023 年 1,216 篇、2024 年 768 篇、2025 年 900 篇、2026 年 1,430 篇。
- NeurIPS 2026 有多少篇深度学习 · generative models and autoencoders论文？
- NeurIPS 2026 有 349 篇深度学习 · generative models and autoencoders论文，上一届是 240 篇。
- ICLR 2026 有多少篇深度学习 · generative models and autoencoders论文？
- ICLR 2026 有 303 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。
- ICML 2026 有多少篇深度学习 · generative models and autoencoders论文？
- ICML 2026 有 604 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。
- CVPR 2026 有多少篇深度学习 · generative models and autoencoders论文？
- CVPR 2026 有 174 篇深度学习 · generative models and autoencoders论文，上一届是 110 篇。
- 哪个会议的深度学习 · generative models and autoencoders论文最多？
- NeurIPS，2023–2026 年共 1,714 篇。