概念解释论文趋势 2023–2026
TCAV 等
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 342 篇被归入该主题的论文。
主要结论
- 概念解释论文从 2023 年的 91 篇增长到 2026 年的 117 篇，三年间扩大到约 1.3 倍。
- NeurIPS 是发概念解释论文最多的会议，2023–2026 年共 134 篇，占四个会议总量的 39%。
- 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 4 篇增至 2026 年的 23 篇。
- 在「可解释性」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的机制解释是 8.1 倍，概念解释是 1.3 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 48 | 9 | 27 | 7 | 91 |
| 2024 | 21 | 9 | 20 | 13 | 63 |
| 2025 | 25 | 19 | 11 | 16 | 71 |
| 2026 | 40 | 24 | 20 | 33 | 117 |
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 2026CENDRe: Concept Extraction with Natural Domain Representations
- ICML 2026Evidential Copula Concept Embedding Models
- ICLR 2026Decoupling the Class Label and the Target Concept in Machine Unlearning
- CVPR 2026Agile Deliberation Concept Deliberation for Subjective Visual Classification
- NeurIPS 2025An Analysis of Concept Bottleneck Models: Measuring, Understanding, and Mitigating the Impact of Noisy Annotations
- ICML 2025Concept-Centric Token Interpretation for Vector-Quantized Generative Models
- ICLR 2025Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning
- CVPR 2025Discovering Fine-Grained Visual-Concept Relations by Disentangled Optimal Transport Concept Bottleneck Models
- NeurIPS 2024[Re] On the Reproducibility of Post-Hoc Concept Bottleneck Models
- ICML 2024ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
- ICLR 2024AttEXplore: Attribution for Explanation with model parameters eXploration
- CVPR 2024Fine-Grained Bipartite Concept Factorization for Clustering
- NeurIPS 2023[Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods
- ICML 2023A Closer Look at the Intervention Procedure of Concept Bottleneck Models
- ICLR 2023Concept Gradient: Concept-based Interpretation Without Linear Assumption
- CVPR 2023CRAFT: Concept Recursive Activation FacTorization for Explainability
- NeurIPS 2026Concept frustration: Aligning human concepts and machine representations
- ICML 2026On the Variability of Concept Activation Vectors
- ICLR 2026Hierarchical Concept-based Interpretable Models
- CVPR 2026DCoAR Deep Concept Injection into Unified Autoregressive Models for Personalized
全部概念解释论文
共 13 篇，第 1 / 1 页
- CVPR 2024Adversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners
- CVPR 2024CLiC: Concept Learning in Context
- CVPR 2024Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods
- CVPR 2024ConCon-Chi: Concept-Context Chimera Benchmark for Personalized Vision-Language Tasks
- CVPR 2024CosalPure: Learning Concept from Group Images for Robust Co-Saliency Detection
- CVPR 2024Discovering and Mitigating Visual Biases through Keyword Explanation
- CVPR 2024Fine-Grained Bipartite Concept Factorization for Clustering
- CVPR 2024Incremental Residual Concept Bottleneck Models
- CVPR 2024Label-Efficient Group Robustness via Out-of-Distribution Concept Curation
- CVPR 2024MACE: Mass Concept Erasure in Diffusion Models
- CVPR 2024MCPNet: An Interpretable Classifier via Multi-Level Concept Prototypes
- CVPR 2024Naturally Supervised 3D Visual Grounding with Language-Regularized Concept Learners
- CVPR 2024Neural Redshift: Random Networks are not Random Functions
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 查概念解释在 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": "concept-based-explanation"}
常见问题
- 2023–2026 年四大会议一共有多少篇概念解释论文？
- 共 342 篇，按年份分别是 2023 年 91 篇、2024 年 63 篇、2025 年 71 篇、2026 年 117 篇。
- NeurIPS 2026 有多少篇概念解释论文？
- NeurIPS 2026 有 40 篇概念解释论文，上一届是 25 篇。
- ICLR 2026 有多少篇概念解释论文？
- ICLR 2026 有 24 篇概念解释论文，上一届是 19 篇。
- ICML 2026 有多少篇概念解释论文？
- ICML 2026 有 20 篇概念解释论文，上一届是 11 篇。
- CVPR 2026 有多少篇概念解释论文？
- CVPR 2026 有 33 篇概念解释论文，上一届是 16 篇。
- 哪个会议的概念解释论文最多？
- NeurIPS，2023–2026 年共 134 篇。