因果推荐论文趋势 2023–2026

去偏与 uplift

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 548 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

因果推荐论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023261931783
20245721396123
20256932492152
202675435616190

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

全部因果推荐论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 548 篇，第 7 / 11 页

  1. NeurIPS 2025Distributed mediation analysis with communication efficiency
  2. NeurIPS 2025Do-PFN: In-Context Learning for Causal Effect Estimation
  3. NeurIPS 2025Efficient Knowledge Transfer in Federated Recommendation for Joint Venture Ecosystem
  4. NeurIPS 2025Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning
  5. NeurIPS 2025Estimation of Treatment Effects in Extreme and Unobserved Data
  6. NeurIPS 2025Fading to Grow: Growing Preference Ratios via Preference Fading Discrete Diffusion for Recommendation
  7. NeurIPS 2025Fast exact recovery of noisy matrix from few entries: the infinity norm approach
  8. NeurIPS 2025Faster Generic Identification in Tree-Shaped Structural Causal Models
  9. NeurIPS 2025From Black-box to Causal-box: Towards Building More Interpretable Models
  10. NeurIPS 2025Graph-Theoretic Insights into Bayesian Personalized Ranking for Recommendation
  11. NeurIPS 2025HPSERec: A Hierarchical Partitioning and Stepwise Enhancement Framework for Long-tailed Sequential Recommendation
  12. NeurIPS 2025Identifying Macro Causal Effects in C-DMGs over DMGs
  13. NeurIPS 2025It’s Hard to Be Normal: The Impact of Noise on Structure-agnostic Estimation
  14. NeurIPS 2025Make Information Diffusion Explainable: LLM-based Causal Framework for Diffusion Prediction
  15. NeurIPS 2025Measure-Theoretic Anti-Causal Representation Learning
  16. NeurIPS 2025Meta-D2AG: Causal Graph Learning with Interventional Dynamic Data
  17. NeurIPS 2025Negative Feedback Really Matters: Signed Dual-Channel Graph Contrastive Learning Framework for Recommendation
  18. NeurIPS 2025Neuro-Spectral Architectures for Causal Physics-Informed Networks
  19. NeurIPS 2025Non-Markovian Discrete Diffusion with Causal Language Models
  20. NeurIPS 2025Non-Stationary Structural Causal Bandits
  21. NeurIPS 2025ORBIT - Open Recommendation Benchmark for Reproducible Research with Hidden Tests
  22. NeurIPS 2025P-Law: Predicting Quantitative Scaling Law with Entropy Guidance in Large Recommendation Models
  23. NeurIPS 2025Path-Enhanced Contrastive Learning for Recommendation
  24. NeurIPS 2025Photography Perspective Composition: Towards Aesthetic Perspective Recommendation
  25. NeurIPS 2025Pinpointing Attention-Causal Communication in Language Models
  26. NeurIPS 2025Practical do-Shapley Explanations with Estimand-Agnostic Causal Inference
  27. NeurIPS 2025Prediction-Powered Causal Inferences
  28. NeurIPS 2025PUATE: Efficient ATE Estimation from Treated (Positive) and Unlabeled Units
  29. NeurIPS 2025Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization
  30. NeurIPS 2025Relaxing partition admissibility in Cluster-DAGs: a causal calculus with arbitrary variable clustering
  31. NeurIPS 2025Reward-oriented Causal Representation Learning
  32. NeurIPS 2025SPARTAN: A Sparse Transformer World Model Attending to What Matters
  33. NeurIPS 2025SPOT-Trip: Dual-Preference Driven Out-of-Town Trip Recommendation
  34. NeurIPS 2025Think before Recommendation: Autonomous Reasoning-enhanced Recommender
  35. NeurIPS 2025Towards Identifiability of Hierarchical Temporal Causal Representation Learning
  36. NeurIPS 2025Towards Single-Source Domain Generalized Object Detection via Causal Visual Prompts
  37. NeurIPS 2025Transferring Causal Effects using Proxies
  38. NeurIPS 2025Tree of Preferences for Diversified Recommendation
  39. NeurIPS 2025Turning Sand to Gold: Recycling Data to Bridge On-Policy and Off-Policy Learning via Causal Bound
  40. NeurIPS 2025TV-Rec: Time-Variant Convolutional Filter for Sequential Recommendation
  41. NeurIPS 2025Universal Causal Inference in a Topos
  42. NeurIPS 2025When Causal Dynamics Matter: Adapting Causal Strategies through Meta-Aware Interventions
  43. CVPR 2024Bi-Causal: Group Activity Recognition via Bidirectional Causality
  44. CVPR 2024CaDeT: a Causal Disentanglement Approach for Robust Trajectory Prediction in Autonomous Driving
  45. CVPR 2024Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian Detection
  46. CVPR 2024CausalPC: Improving the Robustness of Point Cloud Classification by Causal Effect Identification
  47. CVPR 2024MuseChat: A Conversational Music Recommendation System for Videos
  48. CVPR 2024ProMark: Proactive Diffusion Watermarking for Causal Attribution
  49. ICLR 2024A Neural Framework for Generalized Causal Sensitivity Analysis
  50. ICLR 2024Adversarial Causal Bayesian Optimization

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 查因果推荐在 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": "causal-recommendation"}

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。

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