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 1,430 篇，第 28 / 29 页

  1. NeurIPS 2026Scattered by Design: Why Per-Output Pruning Resists Structured Compression
  2. NeurIPS 2026Seeing the Unseen: Unified Visible–Invisible Motion for Physically Consistent Video Generation
  3. NeurIPS 2026Selective Safety Steering via Value-Filtered Decoding
  4. NeurIPS 2026Semantic Optimal Transport for Sparse Autoencoder Feature Matching and Circuit Compression
  5. NeurIPS 2026ShiftRAG: Bypassing the Textual Bottleneck via Decoupled Learning and Continuous Soft Tokens
  6. NeurIPS 2026SOLAR: AI-Powered Speed-of-Light Performance Analysis
  7. NeurIPS 2026SP$^3$: Spherical Priors for Plug-and-Play Restoration
  8. NeurIPS 2026Sparse Biological Features Reveal Early Functional Commitment in Diffusion Protein Language Models
  9. NeurIPS 2026Sparse Koopman Autoencoders Identify Local Dynamical Regimes in Multibasin Systems
  10. NeurIPS 2026Spectral-Sphere-Constrained Hyper-Connections
  11. NeurIPS 2026Split-and-scale Latent 3D Representations
  12. NeurIPS 2026Stability and Diversity of Networked Self-Consuming Generative Ecosystems
  13. NeurIPS 2026Stable and Granular Policy Optimization for Generative Recommendation
  14. NeurIPS 2026Stable GFlowNets with Probabilistic Guarantees
  15. NeurIPS 2026Stein Transport for Generative Modeling
  16. NeurIPS 2026StiCAS: Compositional Activation Steering via Stiefel Manifold Coordinate Transport
  17. NeurIPS 2026Stochastic Heat Diffusion Models
  18. NeurIPS 2026Stochastic Interpolants via Conditional Dependent Coupling
  19. NeurIPS 2026Structural Rationale Distillation via Reasoning Space Compression
  20. NeurIPS 2026Structured Coupling for Flow Matching
  21. NeurIPS 2026Supervised Distributional Reduction via Optimal Transport and Dependence Maximization
  22. NeurIPS 2026Support Before Frequency in Discrete Diffusion
  23. NeurIPS 2026Survive or Collapse: The Asymmetric Roles of Data Gating and Reward Grounding in Self-Play RL
  24. NeurIPS 2026SVG-3D: Mining Decision Boundaries with Generative Splatting Priors for Zero-Shot 3D Classification
  25. NeurIPS 2026SynMQG: Disentanglement and Mutual-Information Optimization for Synergistic Multi-modal Question Generation
  26. NeurIPS 2026Tabular Foundation Model for Generative Modelling
  27. NeurIPS 2026Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning
  28. NeurIPS 2026Taming Generative Co-Folding Prior for Molecular Docking with Diffusion Bridge
  29. NeurIPS 2026Temporal Backtracking Search for Test-time Generative Video Reasoning
  30. NeurIPS 2026Temporal Island Sparse Autoencoders for Interpreting Clinical Time-Series Models
  31. NeurIPS 2026Temporal Pair Consistency for Flow Matching
  32. NeurIPS 2026Tessellations of Semi-Discrete Flow Matching
  33. NeurIPS 2026The $1/\mathcal{W}$ Law: Context Length is the Dominant Energy Lever in LLM Inference Fleets
  34. NeurIPS 2026The balance between feature learning and collapse in generative dynamical systems
  35. NeurIPS 2026The Benefits of Temporal Correlations: SGD Efficiently Learns k-Juntas from Random Walks
  36. NeurIPS 2026The Butterfly Effect in Reasoning: Branch-Structured Distributional Memory for Stochastic Agents
  37. NeurIPS 2026The Expressivity Boundary of Probabilistic Circuits: A Comparison with Large Language Models
  38. NeurIPS 2026The Fault in Our Metrics: Revisiting Generative Model Evaluation with Chamfer Distance
  39. NeurIPS 2026The Rate-Distortion-Polysemanticity Tradeoff in SAEs
  40. NeurIPS 2026The Weight Gram Matrix Captures Sequential Feature Linearization in Deep Networks
  41. NeurIPS 2026Towards Unified Memory Adaptation for LLM Agents: Textual, Latent, and Parametric Pathways
  42. NeurIPS 2026TRACER: Token ReAssignment for Concept ERasure in Generative Recommendation
  43. NeurIPS 2026Training-Free Generative Sampling via Moment-Matched Score Smoothing
  44. NeurIPS 2026Transporting Quantiles to Codebook: Scalable Vector Quantization without Codebook Collapse
  45. NeurIPS 2026Tree-Sliced Orlicz Integral Probability Metric
  46. NeurIPS 2026Trie-Aware Transformers for Generative Recommendation
  47. NeurIPS 2026Trivialized Generative Models on Lie Groups
  48. NeurIPS 2026Tunable Latent Generative Priors for Compressed Sensing and Inverse Problems
  49. NeurIPS 2026Twisted Schrödinger Bridge Matching
  50. NeurIPS 2026Two Speeds of Learning: A Representation-Readout Decomposition of Grokking and Double Descent

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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