Feature Attribution papers, 2023–2026

Key findings

• Feature Attribution went from 118 papers in 2023 to 219 in 2026, roughly 1.9x in three years.
• NeurIPS publishes the most Feature Attribution work: 193 papers from 2023 to 2026, 28% of the four-venue total.
• The fastest-growing overlap is with Theory · learning theory: papers tagged with both rose from 1 in 2023 to 14 in 2026.
• Among the 5 topics under Interpretability, it ranks #1 by 2026 paper count; the fastest grower in the group, Mechanistic Interpretability, is up 8.1x versus 1.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026ADAPT: Hybrid Prompt Optimization for LLM Feature Visualization
• ICML 2026Activation with Intrinsic-Extrinsic Consensus
• ICLR 2026AnyUp: Universal Feature Upsampling
• CVPR 2026A Training-Free Style-Personalization via SVD-Based Feature Decomposition
• NeurIPS 2025Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks
• ICML 2025BCE vs. CE in Deep Feature Learning
• ICLR 2025A Differentiable Rank-Based Objective for Better Feature Learning
• CVPR 2025A Simple Data Augmentation for Feature Distribution Skewed Federated Learning
• NeurIPS 2024$\texttt{dattri}$: A Library for Efficient Data Attribution
• ICML 2024Asymptotics of feature learning in two-layer networks after one gradient-step
• ICLR 2024An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks
• CVPR 2024DYSON: Dynamic Feature Space Self-Organization for Online Task-Free Class Incremental Learning
• NeurIPS 2023$\mathcal{M}^4$: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models
• ICML 2023Decoding Layer Saliency in Language Transformers
• ICLR 2023Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN?
• CVPR 2023A Practical Upper Bound for the Worst-Case Attribution Deviations
• NeurIPS 2026Adaptive Feature Propagation for Attribute-Missing Graph Clustering
• ICML 2026Aggregate Models, Not Explanations: Improving Feature Importance Estimation
• ICLR 2026Attribution-Guided Decoding
• CVPR 2026FBTA Enabling Single-GPU End-to-End Gigapixel WSI Classification with Feature Bridging

All Feature Attribution papers

193 papers, page 4 of 4

151. NeurIPS 2024Parallel Backpropagation for Shared-Feature Visualization
152. NeurIPS 2024Personalized Federated Learning via Feature Distribution Adaptation
153. NeurIPS 2024Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
154. NeurIPS 2024Provable Benefit of Cutout and CutMix for Feature Learning
155. NeurIPS 2024ProxyFusion: Face Feature Aggregation Through Sparse Experts
156. NeurIPS 2024shapiq: Shapley Interactions for Machine Learning
157. NeurIPS 2024Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution
158. NeurIPS 2024SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysis
159. NeurIPS 2024Symmetries in Overparametrized Neural Networks: A Mean Field View
160. NeurIPS 2024The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks
161. NeurIPS 2024The Prevalence of Neural Collapse in Neural Multivariate Regression
162. NeurIPS 2024To Learn or Not to Learn, That is the Question — A Feature-Task Dual Learning Model of Perceptual Learning
163. NeurIPS 2024Training Data Attribution via Approximate Unrolling
164. NeurIPS 2024Understanding Visual Feature Reliance through the Lens of Complexity
165. NeurIPS 2024Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
166. NeurIPS 2024WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
167. NeurIPS 2024Where Do Large Learning Rates Lead Us?
168. NeurIPS 2024You Only Look Around: Learning Illumination-Invariant Feature for Low-light Object Detection
169. NeurIPS 2023$\mathcal{M}^4$: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities and Models
170. NeurIPS 2023A Neural Collapse Perspective on Feature Evolution in Graph Neural Networks
171. NeurIPS 2023A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning
172. NeurIPS 2023Adversarial Learning for Feature Shift Detection and Correction
173. NeurIPS 2023Better Private Linear Regression Through Better Private Feature Selection
174. NeurIPS 2023Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability
175. NeurIPS 2023Error Bounds for Learning with Vector-Valued Random Features
176. NeurIPS 2023Feature Adaptation for Sparse Linear Regression
177. NeurIPS 2023Feature learning via mean-field Langevin dynamics: classifying sparse parities and beyond
178. NeurIPS 2023Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples
179. NeurIPS 2023FedFed: Feature Distillation against Data Heterogeneity in Federated Learning
180. NeurIPS 2023GAIA: Delving into Gradient-based Attribution Abnormality for Out-of-distribution Detection
181. NeurIPS 2023Going Beyond Linear Mode Connectivity: The Layerwise Linear Feature Connectivity
182. NeurIPS 2023Joint Feature and Differentiable $ k $-NN Graph Learning using Dirichlet Energy
183. NeurIPS 2023Learning Curves for Deep Structured Gaussian Feature Models
184. NeurIPS 2023Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles
185. NeurIPS 2023Model and Feature Diversity for Bayesian Neural Networks in Mutual Learning
186. NeurIPS 2023Reading Relevant Feature from Global Representation Memory for Visual Object Tracking
187. NeurIPS 2023SHAP-IQ: Unified Approximation of any-order Shapley Interactions
188. NeurIPS 2023SmoothHess: ReLU Network Feature Interactions via Stein's Lemma
189. NeurIPS 2023Stability Guarantees for Feature Attributions with Multiplicative Smoothing
190. NeurIPS 2023TexQ: Zero-shot Network Quantization with Texture Feature Distribution Calibration
191. NeurIPS 2023Towards Efficient Pre-Trained Language Model via Feature Correlation Distillation
192. NeurIPS 2023Towards Hybrid-grained Feature Interaction Selection for Deep Sparse Network
193. NeurIPS 2023Towards Stable Backdoor Purification through Feature Shift Tuning

FAQ

How many Feature Attribution papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

695 in total: 118 in 2023, 168 in 2024, 190 in 2025, 219 in 2026.

How many Feature Attribution papers are at NeurIPS 2026?

NeurIPS 2026 has 61 Feature Attribution papers, versus 57 the year before.

How many Feature Attribution papers are at ICLR 2026?

ICLR 2026 has 53 Feature Attribution papers, versus 42 the year before.

How many Feature Attribution papers are at ICML 2026?

ICML 2026 has 56 Feature Attribution papers, versus 51 the year before.

How many Feature Attribution papers are at CVPR 2026?

CVPR 2026 has 49 Feature Attribution papers, versus 40 the year before.

Which conference publishes the most Feature Attribution papers?

NeurIPS, with 193 papers from 2023 to 2026.