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 4,314 篇，第 6 / 87 页
- ICLR 2026Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search
- ICLR 2026Entering the Era of Discrete Diffusion Models: A Benchmark for Schrödinger Bridges and Entropic Optimal Transport
- ICLR 2026ERTACache: Error Rectification and Timesteps Adjustment for Efficient Diffusion
- ICLR 2026Escaping Model Collapse via Synthetic Data Verification: Near-term Improvements and Long-term Convergence
- ICLR 2026Evaluating GFlowNet from partial episodes for stable and flexible policy-based training
- ICLR 2026Everything in Its Place: Benchmarking Spatial Intelligence of Text-to-Image Models
- ICLR 2026FantasyWorld: Geometry-Consistent World Modeling via Unified Video and 3D Prediction
- ICLR 2026FAPO: Flawed-Aware Policy Optimization for Efficient and Reliable Reasoning
- ICLR 2026FAST‑DIPS: Adjoint‑Free Analytic Steps and Hard‑Constrained Likelihood Correction for Diffusion‑Prior Inverse Problems
- ICLR 2026FastFlow: Accelerating The Generative Flow Matching Models with Bandit Inference
- ICLR 2026FilMaster: Bridging Cinematic Principles and Generative AI for Automated Film Generation
- ICLR 2026Finite-Time Convergence Analysis of ODE-based Generative Models for Stochastic Interpolants
- ICLR 2026FlashDLM: Accelerating Diffusion Language Model Inference via Efficient KV Caching and Guided Diffusion
- ICLR 2026Flow Autoencoders are Effective Protein Tokenizers
- ICLR 2026Flow Matching with Semidiscrete Couplings
- ICLR 2026Flow of Spans: Generalizing Language Models to Dynamic Span-Vocabulary via GFlowNets
- ICLR 2026Flow Straight and Fast in Hilbert Space: Functional Rectified Flow
- ICLR 2026FlowCast: Trajectory Forecasting for Scalable Zero-Cost Speculative Flow Matching
- ICLR 2026FLOWER: A Flow-Matching Solver for Inverse Problems
- ICLR 2026Foresight Diffusion: Improving Sampling Consistency in Predictive Diffusion Models
- ICLR 2026Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models
- ICLR 2026Forward-Learned Discrete Diffusion: Learning how to noise to denoise faster
- ICLR 2026Frayed RoPE and Long Inputs: A Geometric Perspective
- ICLR 2026Frequency-Balanced Retinal Representation Learning with Mutual Information Regularization
- ICLR 2026Frozen Priors, Fluid Forecasts: Prequential Uncertainty for Low-Data Deployment with Pretrained Generative Models
- ICLR 2026FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models
- ICLR 2026G4Splat: Geometry-Guided Gaussian Splatting with Generative Prior
- ICLR 2026GAR: Generative Adversarial Reinforcement Learning for Formal Theorem Proving
- ICLR 2026GAS: Enhancing Reward-Cost Balance of Generative Model-assisted Offline Safe RL
- ICLR 2026Gauge Flow Matching: Efficient Constrained Generative Modeling over General Convex Set and Beyond
- ICLR 2026GCGNet: Graph-Consistent Generative Network for Time Series Forecasting with Exogenous Variables
- ICLR 2026GDGB: A Benchmark for Generative Dynamic Text-Attributed Graph Learning
- ICLR 2026GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes
- ICLR 2026Gen-DFL: Decision-Focused Generative Learning for Robust Decision Making
- ICLR 2026GenCape: Structure-Inductive Generative Modeling for Category-Agnostic Pose Estimation
- ICLR 2026GenCompositor: Generative Video Compositing with Diffusion Transformer
- ICLR 2026GenCtrl -- A Formal Controllability Toolkit for Generative Models
- ICLR 2026GenDR: Lighten Generative Detail Restoration
- ICLR 2026Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds
- ICLR 2026Generalization of Diffusion Models Arises with a Balanced Representation Space
- ICLR 2026Generalizing Linear Autoencoder Recommenders with Decoupled Expected Quadratic Loss
- ICLR 2026Generative Adversarial Reasoner: Enhancing LLM Reasoning with Adversarial Reinforcement Learning
- ICLR 2026Generative Bayesian Optimization: Generative Models as Acquisition Functions
- ICLR 2026Generative Blocks World: Moving Things Around in Pictures
- ICLR 2026Generative Human Geometry Distribution
- ICLR 2026Generative Modeling from Black-Box Corruptions via Self-Consistent Stochastic Interpolants
- ICLR 2026Generative Universal Verifier as Multimodal Meta-Reasoner
- ICLR 2026Generative Value Conflicts Reveal LLM Priorities
- ICLR 2026Generative View Stitching
- ICLR 2026GenSR: Symbolic regression based on equation generative space
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。