深度学习 · generative models and autoencoders论文趋势 2023–2026

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。

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 9 / 29 页

401. ICLR 2026Scaling Speech Tokenizers with Diffusion Autoencoders
402. ICLR 2026ScalingCache: Extreme Acceleration of DiTs through Difference Scaling and Dynamic Interval Caching
403. ICLR 2026SCOPED: Score–Curvature Out-of-distribution Proximity Evaluator for Diffusion
404. ICLR 2026Score Distillation Beyond Acceleration: Generative Modeling from Corrupted Data
405. ICLR 2026Self-Speculative Decoding Accelerates Lossless Inference in Any-Order and Any-Subset Autoregressive Models
406. ICLR 2026Self-Speculative Masked Diffusions
407. ICLR 2026SERUM: Simple, Efficient, Robust, and Unifying Marking for Diffusion-based Image Generation
408. ICLR 2026SESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows
409. ICLR 2026SFBD-OMNI: Bridge models for lossy measurement restoration with limited clean samples
410. ICLR 2026Shift-and-Sum Quantization for Visual Autoregressive Models
411. ICLR 2026Shrinking Proteins with Diffusion
412. ICLR 2026SIGMA-GEN: STRUCTURE AND IDENTITY GUIDED MULTI-SUBJECT ASSEMBLY FOR IMAGE GENERATION
413. ICLR 2026Signal in the Noise: Polysemantic Interference Transfers and Predicts Cross-Model Influence
414. ICLR 2026SimpleFold: Folding Proteins is Simpler than You Think
415. ICLR 2026SimpleGVR: A Simple Baseline for Latent-Cascaded Generative Video Super-Resolution
416. ICLR 2026SoFlow: Solution Flow Models for One-Step Generative Modeling
417. ICLR 2026SONA: Learning Conditional, Unconditional, and Matching-Aware Discriminator
418. ICLR 2026SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling
419. ICLR 2026Sparse Autoencoders Trained on the Same Data Learn Different Features
420. ICLR 2026Sparse CLIP: Co-Optimizing Interpretability and Performance in Contrastive Learning
421. ICLR 2026SparseD: Sparse Attention for Diffusion Language Models
422. ICLR 2026SpatialHand: Generative Object Manipulation from 3D Prespective
423. ICLR 2026Spatially Informed Autoencoders for Interpretable Visual Representation Learning
424. ICLR 2026SpecBranch: Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism
425. ICLR 2026Specialization after Generalization: Towards Understanding Test-Time Training in Foundation Models
426. ICLR 2026SPEED: Scalable, Precise, and Efficient Concept Erasure for Diffusion Models
427. ICLR 2026SpikeGen: Decoupled “Rods and Cones” Visual Representation Processing with Latent Generative Framework
428. ICLR 2026Stage-wise Dynamics of Classifier-Free Guidance in Diffusion Models
429. ICLR 2026STaMP: Sequence Transformation and Mixed Precision for Low-Precision Activation Quantization
430. ICLR 2026STORK: Faster Diffusion and Flow Matching Sampling by Resolving both Stiffness and Structure-Dependence
431. ICLR 2026Structured Flow Autoencoders: Learning Structured Probabilistic Representations with Flow Matching
432. ICLR 2026Subquadratic Algorithms and Hardness for Attention with Any Temperature
433. ICLR 2026Symmetric Space Learning for Combinatorial Generalization
434. ICLR 2026Synthesising Counterfactual Explanations via Label-Conditional Gaussian Mixture Variational Autoencoders
435. ICLR 2026Synthetic History: Evaluating Visual Representations of the Past in Diffusion Models
436. ICLR 2026Tactic: Adaptive Sparse Attention with Clustering and Distribution Fitting for Long-Context LLMs
437. ICLR 2026Taming Polysemanticity in LLMs: Theory-Grounded Feature Recovery via Sparse Autoencoders
438. ICLR 2026Taming Score-Based Denoisers in ADMM: A Convergent Plug-and-Play Framework
439. ICLR 2026TAVAE: A VAE with Adaptable Priors Explains Contextual Modulation in the Visual Cortex
440. ICLR 2026Teaching Metric Distance to Discrete Autoregressive Language Models
441. ICLR 2026Temporal Sparse Autoencoders: Leveraging the Sequential Nature of Language for Interpretability
442. ICLR 2026Terminal Velocity Matching
443. ICLR 2026Test-Time Scaling with Reflective Generative Model
444. ICLR 2026Texture Vector-Quantization and Reconstruction Aware Prediction for Generative Super-Resolution
445. ICLR 2026The Diffusion Duality, Chapter II: $\Psi$-Samplers and Efficient Curriculum
446. ICLR 2026The Intricate Dance of Prompt Complexity, Quality, Diversity and Consistency in T2I Models
447. ICLR 2026The Lattice Geometry of Neural Network Quantization: A Short Equivalence Proof of GPTQ and Babai's Algorithm
448. ICLR 2026The Price of Amortized inference in Sparse Autoencoders
449. ICLR 2026The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology
450. ICLR 2026The Spacetime of Diffusion Models: An Information Geometry Perspective

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。