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

342 papers, page 5 of 7

201. CVPR 2024Neural Redshift: Random Networks are not Random Functions
202. ICLR 2024AttEXplore: Attribution for Explanation with model parameters eXploration
203. ICLR 2024Classification with Conceptual Safeguards
204. ICLR 2024Concept Bottleneck Generative Models
205. ICLR 2024Effective pruning of web-scale datasets based on complexity of concept clusters
206. ICLR 2024Energy-Based Concept Bottleneck Models: Unifying Prediction, Concept Intervention, and Probabilistic Interpretations
207. ICLR 2024Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
208. ICLR 2024On Error Propagation of Diffusion Models
209. ICLR 2024RAPPER: Reinforced Rationale-Prompted Paradigm for Natural Language Explanation in Visual Question Answering
210. ICLR 2024Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
211. ICML 2024A Geometric Explanation of the Likelihood OOD Detection Paradox
212. ICML 2024Active Statistical Inference
213. ICML 2024An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning
214. ICML 2024Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance
215. ICML 2024ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
216. ICML 2024Easing Concept Bleeding in Diffusion via Entity Localization and Anchoring
217. ICML 2024EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
218. ICML 2024Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
219. ICML 2024Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
220. ICML 2024Gradient-based Visual Explanation for Transformer-based CLIP
221. ICML 2024Learning to Intervene on Concept Bottlenecks
222. ICML 2024Local vs. Global Interpretability: A Computational Complexity Perspective
223. ICML 2024On a Combinatorial Problem Arising in Machine Teaching
224. ICML 2024On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box
225. ICML 2024One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment
226. ICML 2024RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
227. ICML 2024Spider: A Unified Framework for Context-dependent Concept Segmentation
228. ICML 2024Towards Compositionality in Concept Learning
229. ICML 2024Understanding Inter-Concept Relationships in Concept-Based Models
230. ICML 2024Why Do You Grok? A Theoretical Analysis on Grokking Modular Addition
231. NeurIPS 2024[Re] On the Reproducibility of Post-Hoc Concept Bottleneck Models
232. NeurIPS 2024A Concept-Based Explainability Framework for Large Multimodal Models
233. NeurIPS 2024A Neural Network Approach for Efficiently Answering Most Probable Explanation Queries in Probabilistic Models
234. NeurIPS 2024A theoretical design of concept sets: improving the predictability of concept bottleneck models
235. NeurIPS 2024Auditing Local Explanations is Hard
236. NeurIPS 2024Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?
237. NeurIPS 2024Coarse-to-Fine Concept Bottleneck Models
238. NeurIPS 2024Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
239. NeurIPS 2024Do LLMs dream of elephants (when told not to)? Latent concept association and associative memory in transformers
240. NeurIPS 2024From Causal to Concept-Based Representation Learning
241. NeurIPS 2024Improving Decision Sparsity
242. NeurIPS 2024Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents
243. NeurIPS 2024Interpretable Concept-Based Memory Reasoning
244. NeurIPS 2024Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
245. NeurIPS 2024Neural Concept Binder
246. NeurIPS 2024PaCE: Parsimonious Concept Engineering for Large Language Models
247. NeurIPS 2024Relational Concept Bottleneck Models
248. NeurIPS 2024Stochastic Concept Bottleneck Models
249. NeurIPS 2024Towards Multi-dimensional Explanation Alignment for Medical Classification
250. NeurIPS 2024Training for Stable Explanation for Free

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.