On the public citation graph

Focusex: Generalizable Explanation Guided Learning Through Noise Reduction and Fine-Grained Localization

https://doi.org/10.2139/ssrn.5403119
0 signed · 32 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-1-4757-3264-1openalex-snapshot
The Nature of Statistical Learning Theory
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1016/j.aei.2025.103227openalex-snapshot
Mitigating potential risk via counterfactual explanation generation in blast-based tunnel construction
inferredcites →https://doi.org/10.1016/j.aei.2025.103277openalex-snapshot
A data-driven metric-based proper orthogonal decomposition method with Shapley Additive Explanations for aerodynamic shape inverse design optimization
inferredcites →https://doi.org/10.1016/j.cviu.2024.103933openalex-snapshot
A novel slime mold algorithm for grayscale and color image contrast enhancement
inferredcites →https://doi.org/10.1016/j.cviu.2025.104304openalex-snapshot
A multi-modal explainability approach for human-aware robots in multi-party conversation
inferredcites →https://doi.org/10.1016/j.cviu.2025.104370openalex-snapshot
Attribute-guided Relevance Propagation for interpreting image classifier based on Deep Neural Networks
inferredcites →https://doi.org/10.1016/j.neucom.2024.128850openalex-snapshot
Graph-enhanced visual representations and question-guided dual attention for visual question answering
inferredcites →https://doi.org/10.1109/cvpr.2017.243openalex-snapshot
Densely Connected Convolutional Networks
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01257openalex-snapshot
Learning to Learn Single Domain Generalization
inferredcites →https://doi.org/10.1109/cvpr52729.2023.00372openalex-snapshot
Are Data-Driven Explanations Robust Against Out-of-Distribution Data?
inferredcites →https://doi.org/10.1109/cvpr52733.2024.01525openalex-snapshot
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
inferredcites →https://doi.org/10.1109/disa.2018.8490530openalex-snapshot
From Machine Learning to Explainable AI
inferredcites →https://doi.org/10.1109/dsaa.2018.00018openalex-snapshot
Explaining Explanations: An Overview of Interpretability of Machine Learning
inferredcites →https://doi.org/10.1109/iccv.2013.208openalex-snapshot
Unbiased Metric Learning: On the Utilization of Multiple Datasets and Web Images for Softening Bias
inferredcites →https://doi.org/10.1109/iccv.2017.74openalex-snapshot
Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
inferredcites →https://doi.org/10.1145/3534678.3539419openalex-snapshot
RES: A Robust Framework for Guiding Visual Explanation
inferredcites →https://doi.org/10.1145/3644073openalex-snapshot
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
inferredcites →https://doi.org/10.1609/aaai.v33i01.33013714openalex-snapshot
MixUp as Locally Linear Out-of-Manifold Regularization
inferredcites →https://doi.org/10.1609/aaai.v34i04.6123openalex-snapshot
Adversarial Domain Adaptation with Domain Mixup
inferredcites →https://doi.org/10.1609/aaai.v36i9.21196openalex-snapshot
Do Feature Attribution Methods Correctly Attribute Features?
inferredcites →https://doi.org/10.18653/v1/n16-3020openalex-snapshot
“Why Should I Trust You?”: Explaining the Predictions of Any Classifier
inferredcites →https://doi.org/10.4230/oasics.dx.2024.27openalex-snapshot
On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
inferredcites →https://doi.org/10.48550/arxiv.1412.6572openalex-snapshot
Explaining and Harnessing Adversarial Examples
inferredcites →https://doi.org/10.48550/arxiv.1705.07874openalex-snapshot
A Unified Approach to Interpreting Model Predictions
inferredcites →https://doi.org/10.48550/arxiv.1804.10745openalex-snapshot
Generalizing Across Domains via Cross-Gradient Training
inferredcites →https://doi.org/10.48550/arxiv.1909.13584openalex-snapshot
Interpretations are useful: penalizing explanations to align neural networks with prior knowledge
inferredcites →https://doi.org/10.48550/arxiv.1911.08731openalex-snapshot
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
inferredcites →https://doi.org/10.48550/arxiv.2007.04612openalex-snapshot
Concept Bottleneck Models
inferredcites →https://doi.org/10.48550/arxiv.2111.14338openalex-snapshot
Improving Deep Learning Interpretability by Saliency Guided Training
inferredcites →https://doi.org/10.48550/arxiv.2409.17370openalex-snapshot
The Overfocusing Bias of Convolutional Neural Networks: A Saliency-Guided Regularization Approach
inferredcites →https://doi.org/10.52202/075280-2172openalex-snapshot
Learning with Explanation Constraints
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.