反事实解释论文趋势 2023–2026
反事实样本
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 90 篇被归入该主题的论文。
主要结论
- 反事实解释论文从 2023 年的 21 篇增长到 2026 年的 26 篇，三年间扩大到约 1.2 倍。
- NeurIPS 是发反事实解释论文最多的会议，2023–2026 年共 31 篇，占四个会议总量的 34%。
- 交叉方向里涨得最快的是反事实公平：同时属于两个主题的论文从 2023 年的 8 篇增至 2026 年的 10 篇。
- 在「可解释性」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的机制解释是 8.1 倍，反事实解释是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 4 | 2 | 8 | 7 | 21 |
| 2024 | 5 | 3 | 10 | 2 | 20 |
| 2025 | 7 | 5 | 9 | 2 | 23 |
| 2026 | 15 | 5 | 4 | 2 | 26 |
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 2026Offloading Score: Measuring AI Reliance through Counterfactual Workflows
- ICML 2026Density-Guided Robust Counterfactual Explanations on Tabular Data under Model Multiplicity
- ICLR 2026Training-free Counterfactual Explanation for Temporal Graph Model Inference
- CVPR 2026Back to the Feature Explaining Video Classifiers with Video Counterfactual
- NeurIPS 2025Causal Explanation-Guided Learning for Organ Allocation
- ICML 2025Exogenous Isomorphism for Counterfactual Identifiability
- ICLR 2025Generating Likely Counterfactuals Using Sum-Product Networks
- CVPR 2025Towards Fine-Grained Interpretability: Counterfactual Explanations for Misclassification with Saliency Partition
- NeurIPS 2024AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties
- ICML 2024CF-OPT: Counterfactual Explanations for Structured Prediction
- ICLR 2024Counterfactual Density Estimation using Kernel Stein Discrepancies
- CVPR 2024Looking Similar Sounding Different: Leveraging Counterfactual Cross-Modal Pairs for Audiovisual Representation Learning
- NeurIPS 2023[Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles
- ICML 2023Counterfactual Analysis in Dynamic Latent State Models
- ICLR 2023Measuring Forgetting of Memorized Training Examples
- CVPR 2023OCTET: Object-Aware Counterfactual Explanations
- NeurIPS 2026Tracing Actual Causes with Counterfactual Witness Maps
- ICML 2026Algorithmic Recourse of In-Context Learning for Tabular Data
- ICLR 2026ATEX-CF: Attack-Informed Counterfactual Explanations for Graph Neural Networks
- CVPR 2026Making the Classification Explanation Faithful to the Confidence Score
全部反事实解释论文
共 13 篇，第 1 / 1 页
- CVPR 2026Back to the Feature Explaining Video Classifiers with Video Counterfactual
- CVPR 2026Making the Classification Explanation Faithful to the Confidence Score
- CVPR 2025Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation
- CVPR 2025Towards Fine-Grained Interpretability: Counterfactual Explanations for Misclassification with Saliency Partition
- CVPR 2024Looking Similar Sounding Different: Leveraging Counterfactual Cross-Modal Pairs for Audiovisual Representation Learning
- CVPR 2024Revisiting Counterfactual Problems in Referring Expression Comprehension
- CVPR 2023Adversarial Counterfactual Visual Explanations
- CVPR 2023Grounding Counterfactual Explanation of Image Classifiers to Textual Concept Space
- CVPR 2023IDGI: A Framework To Eliminate Explanation Noise From Integrated Gradients
- CVPR 2023Masked Images Are Counterfactual Samples for Robust Fine-Tuning
- CVPR 2023OCTET: Object-Aware Counterfactual Explanations
- CVPR 2023Spatial-Temporal Concept Based Explanation of 3D ConvNets
- CVPR 2023Towards Transferable Targeted Adversarial Examples
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 查反事实解释在 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": "counterfactual-explanation"}
常见问题
- 2023–2026 年四大会议一共有多少篇反事实解释论文？
- 共 90 篇，按年份分别是 2023 年 21 篇、2024 年 20 篇、2025 年 23 篇、2026 年 26 篇。
- NeurIPS 2026 有多少篇反事实解释论文？
- NeurIPS 2026 有 15 篇反事实解释论文，上一届是 7 篇。
- ICLR 2026 有多少篇反事实解释论文？
- ICLR 2026 有 5 篇反事实解释论文，上一届是 5 篇。
- ICML 2026 有多少篇反事实解释论文？
- ICML 2026 有 4 篇反事实解释论文，上一届是 9 篇。
- CVPR 2026 有多少篇反事实解释论文？
- CVPR 2026 有 2 篇反事实解释论文，上一届是 2 篇。
- 哪个会议的反事实解释论文最多？
- NeurIPS，2023–2026 年共 31 篇。