On the public citation graph
Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations
0 signed · 77 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.
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known work and none has been retracted — and get a dated CiteStamped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.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-01219-9_47openalex-snapshot
Women Also Snowboard: Overcoming Bias in Captioning Models
inferredcites →https://doi.org/10.1007/978-3-031-14923-8_5openalex-snapshot
“Better” Counterfactuals, Ones People Can Understand: Psychologically-Plausible Case-Based Counterfactuals Using Categorical Features for Explainable AI (XAI)
inferredcites →https://doi.org/10.1007/978-3-319-10602-1_48openalex-snapshot
Microsoft COCO: Common Objects in Context
inferredcites →https://doi.org/10.1007/s00778-021-00671-8openalex-snapshot
Managing bias and unfairness in data for decision support: a survey of machine learning and data engineering approaches to identify and mitigate bias and unfairness within data management and analytics systems
inferredcites →https://doi.org/10.1007/s13222-020-00351-xopenalex-snapshot
Towards Understanding and Arguing with Classifiers: Recent Progress
inferredcites →https://doi.org/10.1016/j.neunet.2019.01.012openalex-snapshot
Continual lifelong learning with neural networks: A review
inferredcites →https://doi.org/10.1037//0021-9010.69.2.334openalex-snapshot
The Hawthorne effect: A reconsideration of the methodological artifact.
inferredcites →https://doi.org/10.1073/pnas.1611835114openalex-snapshot
Overcoming catastrophic forgetting in neural networks
inferredcites →https://doi.org/10.1109/cvpr.2019.01096openalex-snapshot
Attention Branch Network: Learning of Attention Mechanism for Visual Explanation
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01108openalex-snapshot
Don’t Judge an Object by Its Context: Learning to Overcome Contextual Bias
inferredcites →https://doi.org/10.1109/cvpr46437.2021.00545openalex-snapshot
Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation
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/10.1109/iccv.2019.00541openalex-snapshot
Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations
inferredcites →https://doi.org/10.1109/icdm51629.2021.00023openalex-snapshot
GNES: Learning to Explain Graph Neural Networks
inferredcites →https://doi.org/10.1109/icip.2017.8296695openalex-snapshot
TX-CNN: Detecting tuberculosis in chest X-ray images using convolutional neural network
inferredcites →https://doi.org/10.1109/ijcnn48605.2020.9206626openalex-snapshot
Eigen-CAM: Class Activation Map using Principal Components
inferredcites →https://doi.org/10.1109/pacificvis48177.2020.7090openalex-snapshot
ExplainExplore: Visual Exploration of Machine Learning Explanations
inferredcites →https://doi.org/10.1109/tcsvt.2016.2589879openalex-snapshot
Cost-Effective Active Learning for Deep Image Classification
inferredcites →https://doi.org/10.1109/tnnls.2021.3084827openalex-snapshot
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects
inferredcites →https://doi.org/10.1109/tvcg.2016.2598828openalex-snapshot
Squares: Supporting Interactive Performance Analysis for Multiclass Classifiers
inferredcites →https://doi.org/10.1109/tvcg.2017.2744878openalex-snapshot
Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow
inferredcites →https://doi.org/10.1109/tvcg.2018.2864812openalex-snapshot
RuleMatrix: Visualizing and Understanding Classifiers with Rules
inferredcites →https://doi.org/10.1109/tvcg.2019.2934619openalex-snapshot
The What-If Tool: Interactive Probing of Machine Learning Models
inferredcites →https://doi.org/10.1109/tvcg.2019.2934629openalex-snapshot
explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning
inferredcites →https://doi.org/10.1109/tvcg.2021.3114858openalex-snapshot
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks
inferredcites →https://doi.org/10.1109/vast.2017.8585720openalex-snapshot
A Workflow for Visual Diagnostics of Binary Classifiers using Instance-Level Explanations
inferredcites →https://doi.org/10.1109/vast.2017.8585721openalex-snapshot
Understanding Hidden Memories of Recurrent Neural Networks
inferredcites →https://doi.org/10.1145/1656274.1656278openalex-snapshot
The WEKA data mining software
inferredcites →https://doi.org/10.1145/2858036.2858498openalex-snapshot
Local Standards for Sample Size at CHI
inferredcites →https://doi.org/10.1145/2939502.2939503openalex-snapshot
Visual exploration of machine learning results using data cube analysis
inferredcites →https://doi.org/10.1145/3173574.3173582openalex-snapshot
Gender Recognition or Gender Reductionism?
inferredcites →https://doi.org/10.1145/3185517openalex-snapshot
A Review of User Interface Design for Interactive Machine Learning
inferredcites →https://doi.org/10.1145/3196709.3196729openalex-snapshot
Grounding Interactive Machine Learning Tool Design in How Non-Experts Actually Build Models
inferredcites →https://doi.org/10.1145/3196709.3196730openalex-snapshot
Investigating How Experienced UX Designers Effectively Work with Machine Learning
inferredcites →https://doi.org/10.1145/3290605openalex-snapshot
Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems
inferredcites →https://doi.org/10.1145/3301275.3302324openalex-snapshot
Towards human-guided machine learning
inferredcites →https://doi.org/10.1145/3313831.3376177openalex-snapshot
Understanding and Visualizing Data Iteration in Machine Learning
inferredcites →https://doi.org/10.1145/3334480.3382899openalex-snapshot
CNN 101: Interactive Visual Learning for Convolutional Neural Networks
inferredcites →https://doi.org/10.1145/3359152openalex-snapshot
The Principles and Limits of Algorithm-in-the-Loop Decision Making
inferredcites →https://doi.org/10.1145/3359158openalex-snapshot
Dissonance Between Human and Machine Understanding
inferredcites →https://doi.org/10.1145/3359164openalex-snapshot
Efficient Elicitation Approaches to Estimate Collective Crowd Answers
inferredcites →https://doi.org/10.1145/3359313openalex-snapshot
Human-AI Collaboration in Data Science
inferredcites →https://doi.org/10.1145/3377815.3381377openalex-snapshot
Is using deep learning frameworks free?
inferredcites →https://doi.org/10.1145/3387166openalex-snapshot
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
inferredcites →https://doi.org/10.1145/3392826openalex-snapshot
How do Data Science Workers Collaborate? Roles, Workflows, and Tools
inferredcites →https://doi.org/10.1145/3392878openalex-snapshot
Human Factors in Model Interpretability: Industry Practices, Challenges, and Needs
inferredcites →https://doi.org/10.1145/3491102.3502075openalex-snapshot
FlatMagic: Improving Flat Colorization through AI-driven Design for Digital Comic Professionals
inferredcites →https://doi.org/10.1145/3531146.3534639openalex-snapshot
A Review of Taxonomies of Explainable Artificial Intelligence (XAI) Methods
inferredcites →https://doi.org/10.1145/3534678.3539419openalex-snapshot
RES: A Robust Framework for Guiding Visual Explanation
inferredcites →https://doi.org/10.1145/3555590openalex-snapshot
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment
inferredcites →https://doi.org/10.1186/s41074-019-0053-3openalex-snapshot
Attacking convolutional neural network using differential evolution
inferredcites →https://doi.org/10.1609/aaai.v35i2.16269openalex-snapshot
Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation
inferredcites →https://doi.org/10.18653/v1/2021.acl-long.415openalex-snapshot
Learning to Explain: Generating Stable Explanations Fast
inferredcites →https://doi.org/10.2307/3341515openalex-snapshot
Sociological Practice: Linking Theory and Social Research
inferredcites →https://doi.org/10.29333/ajqr/12085openalex-snapshot
The Coding Manual for Qualitative Researchers
inferredcites →https://doi.org/10.3390/s21072514openalex-snapshot
A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning
inferredcites →https://doi.org/10.48550/arxiv.2009.14720openalex-snapshot
DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
inferredcites →https://doi.org/10.48550/arxiv.2107.01372openalex-snapshot
Learning Debiased Representation via Disentangled Feature Augmentation
inferredcites →https://doi.org/10.48550/arxiv.2111.14338openalex-snapshot
Improving Deep Learning Interpretability by Saliency Guided Training
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-031-60049-4_13openalex-snapshot
Accessibility of e-books for Secondary School Students in Ireland and Cyprus
inferred← citeshttps://doi.org/10.1080/10447318.2024.2381929openalex-snapshot
How Explainable AI Affects Human Performance: A Systematic Review of the Behavioural Consequences of Saliency Maps
inferred← citeshttps://doi.org/10.1145/3637288openalex-snapshot
3DPFIX: Improving Remote Novices' 3D Printing Troubleshooting through Human-AI Collaboration Design
inferred← citeshttps://doi.org/10.1145/3640543.3645214openalex-snapshot
Closing the Knowledge Gap in Designing Data Annotation Interfaces for AI-powered Disaster Management Analytic Systems
inferred← citeshttps://doi.org/10.1145/3644073openalex-snapshot
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
inferred← citeshttps://doi.org/10.1145/3654777.3676332openalex-snapshot
ShadowMagic: Designing Human-AI Collaborative Support for Comic Professionals’ Shadowing
inferred← citeshttps://doi.org/10.1145/3797953openalex-snapshot
De-Decay: Defusing Computer Vision Model Degradation through Scalable and Actionable Human-Data Alignment
inferred← citeshttps://doi.org/10.1145/3816965openalex-snapshot
Machine Semiology in Practice: Clinician Strategies for Interpreting AI-Generated Visual Explanations
inferred← citeshttps://doi.org/10.31219/osf.io/ms2kvopenalex-snapshot
How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps
inferred← citeshttps://doi.org/10.7717/peerj-cs.2795openalex-snapshot
Enhancing skin lesion classification: a CNN approach with human baseline comparison
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.