因果推荐论文趋势 2023–2026

主要结论

• 因果推荐论文从 2023 年的 83 篇增长到 2026 年的 190 篇，三年间扩大到约 2.3 倍。
• NeurIPS 是发因果推荐论文最多的会议，2023–2026 年共 227 篇，占四个会议总量的 41%。
• 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 21 篇。
• 在「推荐与广告」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的点击率预测是 2.6 倍，因果推荐是 2.3 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 Characterization of Latent Variable Causal Models Consistent with Observational Data
• ICML 2026A Causal Decomposition Approach for Fair Contextual Multi-Armed Bandits
• ICLR 2026ActiveCQ: Active Estimation of Causal Quantities
• CVPR 2026Breaking Spurious Correlations Uncertainty-Driven Causal Transformers for AU Detection
• NeurIPS 2025CCL: Causal-aware In-context Learning for Out-of-Distribution Generalization
• ICML 2025A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings
• ICLR 2025Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
• CVPR 2025Image Quality Assessment: Investigating Causal Perceptual Effects with Abductive Counterfactual Inference
• NeurIPS 2024Causal Bandits for Linear Structural Equation Models
• ICML 2024A Sparsity Principle for Partially Observable Causal Representation Learning
• ICLR 2024Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
• CVPR 2024MuseChat: A Conversational Music Recommendation System for Videos
• NeurIPS 2023A Causal Framework for Decomposing Spurious Variations
• ICML 2023B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding
• ICLR 2023Calibration Matters: Tackling Maximization Bias in Large-scale Advertising Recommendation Systems
• CVPR 2023CafeBoost: Causal Feature Boost To Eliminate Task-Induced Bias for Class Incremental Learning
• NeurIPS 2026Bridging Image Restoration and Recognition via Causal Mediated Unrolling
• ICML 2026Causal Disentangled Anchor Learning for Scalable Fair Multi-view Clustering
• ICLR 2026Addressing divergent representations from causal interventions on neural networks
• CVPR 2026Bridge Basis-Driven Causal Inference Marries VFMs for Domain Generalization

全部因果推荐论文

共 548 篇，第 1 / 11 页

1. CVPR 2026AdapTok Learning Adaptive and Temporally Causal Video Tokenization in a
2. CVPR 2026Beyond Perceptual Shortcuts Causal-Inspired Debiasing Optimization for Generalizable Video Reasoning
3. CVPR 2026BiomedCCPL Causal Conditional Prompt Learning for Biomedical Vision-Language Models
4. CVPR 2026Breaking Spurious Correlations Uncertainty-Driven Causal Transformers for AU Detection
5. CVPR 2026Bridge Basis-Driven Causal Inference Marries VFMs for Domain Generalization
6. CVPR 2026CaTok Taming Mean Flows for One-Dimensional Causal Image Tokenization
7. CVPR 2026CausalLens Sensitivity-Guided Multi-Head Causal Intervention for Hallucination Mitigation in Large
8. CVPR 2026CGU-Bayes Causal Graph Uncertainty-Guided Bayesian Inference for Domain Generalization
9. CVPR 2026CHAL Causal-guided Hierarchical Anomaly-aware Learning for Moving Infrared Small Target
10. CVPR 2026CIGPose Causal Intervention Graph Neural Network for Whole-Body Pose Estimation
11. CVPR 2026Diagnosing and Repairing Unsafe Channels in Vision-Language Models via Causal
12. CVPR 2026GeneVAR Causal MeanFlow for Autoregressive Gene-to-WSI Tile Synthesis
13. CVPR 2026Learning by Analogy A Causal Framework for Compositional Generalization
14. CVPR 2026Progressive Cross-Modal Causal Intervention for Long-Term Action Recognition
15. CVPR 2026Prototype-based Causal Intervention for Multi-Label Image Classification
16. CVPR 2026Streaming Video Crime Anticipation with Spatio-Temporal Causal Reasoning
17. ICLR 2026ActiveCQ: Active Estimation of Causal Quantities
18. ICLR 2026Addressing divergent representations from causal interventions on neural networks
19. ICLR 2026Adjusting Prediction Model Through Wasserstein Geodesic for Causal Inference
20. ICLR 2026ALM-MTA: Front-Door Causal Multi-Touch Attribution Method for Creator-Ecosystem Optimization
21. ICLR 2026Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning
22. ICLR 2026Beyond Entity Correlations: Disentangling Event Causal Puzzles in Temporal Knowledge Graphs
23. ICLR 2026CARL: Preserving Causal Structure in Representation Learning
24. ICLR 2026Catalog-Native LLM: Speaking Item-ID dialect with Less Entanglement for Recommendation
25. ICLR 2026Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
26. ICLR 2026Causal Interpretation of Neural Network Computations with Contribution Decomposition (CODEC)
27. ICLR 2026Causal Score Conditioning for Multi-Resolution Latent Systems
28. ICLR 2026Causal-Steer: Disentangled Continuous Style Control without Parallel Corpora
29. ICLR 2026Causally Robust Preference Learning with Reasons
30. ICLR 2026Characterization and Learning of Causal Graphs with Latent Confounders and Post-treatment Selection from Interventional Data
31. ICLR 2026Coarse-to-Fine Learning of Dynamic Causal Structures
32. ICLR 2026CollectiveKV: Decoupling and Sharing Collaborative Information in Sequential Recommendation
33. ICLR 2026Conditional Independent Component Analysis For Estimating Causal Structure with Latent Variables
34. ICLR 2026Contextual Causal Bayesian Optimisation
35. ICLR 2026Counterfactual Structural Causal Bandits
36. ICLR 2026Direct Doubly Robust Estimation of Conditional Quantile Contrasts
37. ICLR 2026Distributional Equivalence in Linear Non-Gaussian Latent-Variable Cyclic Causal Models: Characterization and Learning
38. ICLR 2026Embracing Discrete Search: A Reasonable Approach to Causal Structure Learning
39. ICLR 2026Exploratory Causal Inference in SAEnce
40. ICLR 2026Generalization of RLVR Using Causal Reasoning as a Testbed
41. ICLR 2026Heterogeneous Front-Door Effects: Debiased Estimation with Quasi-Oracle Guarantees
42. ICLR 2026How Transformers Learn Causal Structures In-Context: Explainable Mechanism Meets Theoretical Guarantee
43. ICLR 2026Learning Dynamic Causal Graphs Under Parametric Uncertainty via Polynomial Chaos Expansions
44. ICLR 2026Learning Nonlinear Causal Reductions to Explain Reinforcement Learning Policies
45. ICLR 2026Low-pass Personalized Subgraph Federated Recommendation
46. ICLR 2026Matching without Group Barrier for Heterogeneous Treatment Effect Estimation
47. ICLR 2026More Than What Was Chosen: LLM-based Explainable Recommendation Beyond Noisy User Preferences
48. ICLR 2026On Measuring Influence in Avoiding Undesired Future
49. ICLR 2026On the identifiability of causal graphs with multiple environments
50. ICLR 2026Privacy-Protected Causal Survival Analysis Under Distribution Shift

常见问题

2023–2026 年四大会议一共有多少篇因果推荐论文？

共 548 篇，按年份分别是 2023 年 83 篇、2024 年 123 篇、2025 年 152 篇、2026 年 190 篇。

NeurIPS 2026 有多少篇因果推荐论文？

NeurIPS 2026 有 75 篇因果推荐论文，上一届是 69 篇。

ICLR 2026 有多少篇因果推荐论文？

ICLR 2026 有 43 篇因果推荐论文，上一届是 32 篇。

ICML 2026 有多少篇因果推荐论文？

ICML 2026 有 56 篇因果推荐论文，上一届是 49 篇。

CVPR 2026 有多少篇因果推荐论文？

CVPR 2026 有 16 篇因果推荐论文，上一届是 2 篇。

哪个会议的因果推荐论文最多？

NeurIPS，2023–2026 年共 227 篇。