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

每年论文数

各会议论文数

按年份和会议统计

深度学习 · generative models and autoencoders论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
202377678286761,216
2024349174139106768
2025240275275110900
20263493036041741,430

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

全部深度学习 · generative models and autoencoders论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 768 篇，第 5 / 16 页

  1. ICLR 2024Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling
  2. ICLR 2024Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency
  3. ICLR 2024Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments
  4. ICLR 2024Lifting Architectural Constraints of Injective Flows
  5. ICLR 2024Light Schrödinger Bridge
  6. ICLR 2024Lipschitz Singularities in Diffusion Models
  7. ICLR 2024LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses
  8. ICLR 2024Localizing and Editing Knowledge In Text-to-Image Generative Models
  9. ICLR 2024Long-tailed Diffusion Models with Oriented Calibration
  10. ICLR 2024LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
  11. ICLR 2024Machine Unlearning for Image-to-Image Generative Models
  12. ICLR 2024Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
  13. ICLR 2024Manifold Diffusion Fields
  14. ICLR 2024Manifold Preserving Guided Diffusion
  15. ICLR 2024Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners
  16. ICLR 2024MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods
  17. ICLR 2024MiniLLM: Knowledge Distillation of Large Language Models
  18. ICLR 2024Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
  19. ICLR 2024Modelling complex vector drawings with stroke-clouds
  20. ICLR 2024Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
  21. ICLR 2024Multi-Source Diffusion Models for Simultaneous Music Generation and Separation
  22. ICLR 2024Multimarginal Generative Modeling with Stochastic Interpolants
  23. ICLR 2024Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation
  24. ICLR 2024NEFTune: Noisy Embeddings Improve Instruction Finetuning
  25. ICLR 2024Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
  26. ICLR 2024Neural Optimal Transport with General Cost Functionals
  27. ICLR 2024Neural structure learning with stochastic differential equations
  28. ICLR 2024Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data
  29. ICLR 2024Noise-free Score Distillation
  30. ICLR 2024OctoPack: Instruction Tuning Code Large Language Models
  31. ICLR 2024On Error Propagation of Diffusion Models
  32. ICLR 2024On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models
  33. ICLR 2024On the Foundations of Shortcut Learning
  34. ICLR 2024On the Reliability of Watermarks for Large Language Models
  35. ICLR 2024On the Stability of Iterative Retraining of Generative Models on their own Data
  36. ICLR 2024PhyloGFN: Phylogenetic inference with generative flow networks
  37. ICLR 2024Pre-Training and Fine-Tuning Generative Flow Networks
  38. ICLR 2024Provable Compositional Generalization for Object-Centric Learning
  39. ICLR 2024Quality-Diversity through AI Feedback
  40. ICLR 2024R-MAE: Regions Meet Masked Autoencoders
  41. ICLR 2024Raidar: geneRative AI Detection viA Rewriting
  42. ICLR 2024Relay Diffusion: Unifying diffusion process across resolutions for image synthesis
  43. ICLR 2024Revisit and Outstrip Entity Alignment: A Perspective of Generative Models
  44. ICLR 2024Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks
  45. ICLR 2024SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
  46. ICLR 2024Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
  47. ICLR 2024SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
  48. ICLR 2024Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
  49. ICLR 2024Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions
  50. ICLR 2024SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

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"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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