Feature Attribution papers, 2023–2026
Saliency and SHAP
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 695 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 25 | 29 | 21 | 43 | 118 |
| 2024 | 50 | 36 | 47 | 35 | 168 |
| 2025 | 57 | 42 | 51 | 40 | 190 |
| 2026 | 61 | 53 | 56 | 49 | 219 |
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
50 papers, page 1 of 1
- NeurIPS 2024$\texttt{dattri}$: A Library for Efficient Data Attribution
- NeurIPS 2024Benchmarking the Attribution Quality of Vision Models
- NeurIPS 2024Credit Attribution and Stable Compression
- NeurIPS 2024Data-faithful Feature Attribution: Mitigating Unobservable Confounders via Instrumental Variables
- NeurIPS 2024DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection
- NeurIPS 2024Denoising Diffusion Path: Attribution Noise Reduction with An Auxiliary Diffusion Model
- NeurIPS 2024DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning
- NeurIPS 2024Dimension-free deterministic equivalents and scaling laws for random feature regression
- NeurIPS 2024Efficient Sketches for Training Data Attribution and Studying the Loss Landscape
- NeurIPS 2024Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing
- NeurIPS 2024EnOF-SNN: Training Accurate Spiking Neural Networks via Enhancing the Output Feature
- NeurIPS 2024ETO:Efficient Transformer-based Local Feature Matching by Organizing Multiple Homography Hypotheses
- NeurIPS 2024Explanations that reveal all through the definition of encoding
- NeurIPS 2024Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
- NeurIPS 2024Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity
- NeurIPS 2024FUGAL: Feature-fortified Unrestricted Graph Alignment
- NeurIPS 2024Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning
- NeurIPS 2024Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation
- NeurIPS 2024Infinite-Dimensional Feature Interaction
- NeurIPS 2024Is Function Similarity Over-Engineered? Building a Benchmark
- NeurIPS 2024Learning Low-Rank Feature for Thorax Disease Classification
- NeurIPS 2024Learning Successor Features the Simple Way
- NeurIPS 2024MatrixNet: Learning over symmetry groups using learned group representations
- NeurIPS 2024MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers
- NeurIPS 2024Mitigating Biases in Blackbox Feature Extractors for Image Classification Tasks
- NeurIPS 2024Most Influential Subset Selection: Challenges, Promises, and Beyond
- NeurIPS 2024Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization
- NeurIPS 2024NeuroBOLT: Resting-state EEG-to-fMRI Synthesis with Multi-dimensional Feature Mapping
- NeurIPS 2024On Feature Learning in Structured State Space Models
- NeurIPS 2024On the Efficiency of ERM in Feature Learning
- NeurIPS 2024On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
- NeurIPS 2024Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
- NeurIPS 2024Parallel Backpropagation for Shared-Feature Visualization
- NeurIPS 2024Personalized Federated Learning via Feature Distribution Adaptation
- NeurIPS 2024Precise asymptotics of reweighted least-squares algorithms for linear diagonal networks
- NeurIPS 2024Provable Benefit of Cutout and CutMix for Feature Learning
- NeurIPS 2024ProxyFusion: Face Feature Aggregation Through Sparse Experts
- NeurIPS 2024shapiq: Shapley Interactions for Machine Learning
- NeurIPS 2024Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution
- NeurIPS 2024SubjECTive-QA: Measuring Subjectivity in Earnings Call Transcripts' QA Through Six-Dimensional Feature Analysis
- NeurIPS 2024Symmetries in Overparametrized Neural Networks: A Mean Field View
- NeurIPS 2024The Feature Speed Formula: a flexible approach to scale hyper-parameters of deep neural networks
- NeurIPS 2024The Prevalence of Neural Collapse in Neural Multivariate Regression
- NeurIPS 2024To Learn or Not to Learn, That is the Question — A Feature-Task Dual Learning Model of Perceptual Learning
- NeurIPS 2024Training Data Attribution via Approximate Unrolling
- NeurIPS 2024Understanding Visual Feature Reliance through the Lens of Complexity
- NeurIPS 2024Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
- NeurIPS 2024WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
- NeurIPS 2024Where Do Large Learning Rates Lead Us?
- NeurIPS 2024You Only Look Around: Learning Illumination-Invariant Feature for Low-light Object Detection
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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.