Concept-Based Explanation papers, 2023–2026

Key findings

• Concept-Based Explanation went from 91 papers in 2023 to 117 in 2026, roughly 1.3x in three years.
• NeurIPS publishes the most Concept-Based Explanation work: 134 papers from 2023 to 2026, 39% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 4 in 2023 to 23 in 2026.
• Among the 5 topics under Interpretability, it ranks #3 by 2026 paper count; the fastest grower in the group, Mechanistic Interpretability, is up 8.1x versus 1.3x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Concept-Based Explanation papers

91 papers, page 1 of 2

1. CVPR 20233D Concept Learning and Reasoning From Multi-View Images
2. CVPR 2023CRAFT: Concept Recursive Activation FacTorization for Explainability
3. CVPR 2023Grounding Counterfactual Explanation of Image Classifiers to Textual Concept Space
4. CVPR 2023IDGI: A Framework To Eliminate Explanation Noise From Integrated Gradients
5. CVPR 2023Overlooked Factors in Concept-Based Explanations: Dataset Choice, Concept Learnability, and Human Capability
6. CVPR 2023S3C: Semi-Supervised VQA Natural Language Explanation via Self-Critical Learning
7. CVPR 2023Spatial-Temporal Concept Based Explanation of 3D ConvNets
8. ICLR 2023A Minimalist Dataset for Systematic Generalization of Perception, Syntax, and Semantics
9. ICLR 2023Concept Gradient: Concept-based Interpretation Without Linear Assumption
10. ICLR 2023Concept-level Debugging of Part-Prototype Networks
11. ICLR 2023Global Explainability of GNNs via Logic Combination of Learned Concepts
12. ICLR 2023GNNInterpreter: A Probabilistic Generative Model-Level Explanation for Graph Neural Networks
13. ICLR 2023Label-free Concept Bottleneck Models
14. ICLR 2023Neural Systematic Binder
15. ICLR 2023Post-hoc Concept Bottleneck Models
16. ICLR 2023Robust Explanation Constraints for Neural Networks
17. ICML 2023A Category-theoretical Meta-analysis of Definitions of Disentanglement
18. ICML 2023A Closer Look at the Intervention Procedure of Concept Bottleneck Models
19. ICML 2023A Kernel-Based View of Language Model Fine-Tuning
20. ICML 2023A Scalable Frank-Wolfe-Based Algorithm for the Max-Cut SDP
21. ICML 2023Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift
22. ICML 2023Causal Proxy Models for Concept-based Model Explanations
23. ICML 2023Cluster Explanation via Polyhedral Descriptions
24. ICML 2023Concept-based Explanations for Out-of-Distribution Detectors
25. ICML 2023Denoising MCMC for Accelerating Diffusion-Based Generative Models
26. ICML 2023Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding
27. ICML 2023Discover and Cure: Concept-aware Mitigation of Spurious Correlation
28. ICML 2023Facial Expression Recognition with Adaptive Frame Rate based on Multiple Testing Correction
29. ICML 2023Flash: Concept Drift Adaptation in Federated Learning
30. ICML 2023Geometric Clifford Algebra Networks
31. ICML 2023Interpretable Neural-Symbolic Concept Reasoning
32. ICML 2023Lowering the Pre-training Tax for Gradient-based Subset Training: A Lightweight Distributed Pre-Training Toolkit
33. ICML 2023Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal
34. ICML 2023On the Relationship Between Explanation and Prediction: A Causal View
35. ICML 2023Probabilistic Concept Bottleneck Models
36. ICML 2023PWSHAP: A Path-Wise Explanation Model for Targeted Variables
37. ICML 2023Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
38. ICML 2023Robust Explanation for Free or At the Cost of Faithfulness
39. ICML 2023SlotGAT: Slot-based Message Passing for Heterogeneous Graphs
40. ICML 2023The Implicit Regularization of Dynamical Stability in Stochastic Gradient Descent
41. ICML 2023The Virtues of Laziness in Model-based RL: A Unified Objective and Algorithms
42. ICML 2023Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten
43. ICML 2023Towards Trustworthy Explanation: On Causal Rationalization
44. NeurIPS 2023[Re] Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Methods
45. NeurIPS 2023$k$-Means Clustering with Distance-Based Privacy
46. NeurIPS 2023A Dynamical System View of Langevin-Based Non-Convex Sampling
47. NeurIPS 2023A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation
48. NeurIPS 2023A Theory of Transfer-Based Black-Box Attacks: Explanation and Implications
49. NeurIPS 2023A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphs
50. NeurIPS 2023Auxiliary Losses for Learning Generalizable Concept-based Models

FAQ

How many Concept-Based Explanation papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

342 in total: 91 in 2023, 63 in 2024, 71 in 2025, 117 in 2026.

How many Concept-Based Explanation papers are at NeurIPS 2026?

NeurIPS 2026 has 40 Concept-Based Explanation papers, versus 25 the year before.

How many Concept-Based Explanation papers are at ICLR 2026?

ICLR 2026 has 24 Concept-Based Explanation papers, versus 19 the year before.

How many Concept-Based Explanation papers are at ICML 2026?

ICML 2026 has 20 Concept-Based Explanation papers, versus 11 the year before.

How many Concept-Based Explanation papers are at CVPR 2026?

CVPR 2026 has 33 Concept-Based Explanation papers, versus 16 the year before.

Which conference publishes the most Concept-Based Explanation papers?

NeurIPS, with 134 papers from 2023 to 2026.