Haekyu Park
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View article: Interactive Visual Learning for Stable Diffusion
Interactive Visual Learning for Stable Diffusion Open
Diffusion-based generative models' impressive ability to create convincing images has garnered global attention. However, their complex internal structures and operations often pose challenges for non-experts to grasp. We introduce Diffusi…
View article: Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries
Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries Open
We present ConceptEvo, a unified interpretation framework for deep neural networks (DNNs) that reveals the inception and evolution of learned concepts during training. Our work addresses a critical gap in DNN interpretation research, as ex…
View article: FoundWright: A System to Help People Re-find Pages from Their Web-history
FoundWright: A System to Help People Re-find Pages from Their Web-history Open
Re-finding information is an essential activity, however, it can be difficult when people struggle to express what they are looking for. Through a need-finding survey, we first seek opportunities for improving re-finding experiences, and e…
View article: Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion
Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion Open
Diffusion-based generative models' impressive ability to create convincing images has garnered global attention. However, their complex structures and operations often pose challenges for non-experts to grasp. We present Diffusion Explaine…
View article: NeuroMapper: In-browser Visualizer for Neural Network Training
NeuroMapper: In-browser Visualizer for Neural Network Training Open
We present our ongoing work NeuroMapper, an in-browser visualization tool that helps machine learning (ML) developers interpret the evolution of a model during training, providing a new way to monitor the training process and visually disc…
View article: Explaining Website Reliability by Visualizing Hyperlink Connectivity
Explaining Website Reliability by Visualizing Hyperlink Connectivity Open
As the information on the Internet continues growing exponentially, understanding and assessing the reliability of a website is becoming increasingly important. Misinformation has far-ranging repercussions, from sowing mistrust in media to…
View article: Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries
Concept Evolution in Deep Learning Training: A Unified Interpretation Framework and Discoveries Open
We present ConceptEvo, a unified interpretation framework for deep neural networks (DNNs) that reveals the inception and evolution of learned concepts during training. Our work addresses a critical gap in DNN interpretation research, as ex…
View article: NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in Deep Neural Networks Open
Existing research on making sense of deep neural networks often focuses on neuron-level interpretation, which may not adequately capture the bigger picture of how concepts are collectively encoded by multiple neurons. We present NeuroCarto…
View article: NeuroCartography: Scalable Automatic Visual Summarization of Concepts in\n Deep Neural Networks
NeuroCartography: Scalable Automatic Visual Summarization of Concepts in\n Deep Neural Networks Open
Existing research on making sense of deep neural networks often focuses on\nneuron-level interpretation, which may not adequately capture the bigger\npicture of how concepts are collectively encoded by multiple neurons. We\npresent NeuroCa…
View article: Quantifying the Impact of Human Capital, Job History, and Language Factors on Job Seniority with a Large-scale Analysis of Resumes
Quantifying the Impact of Human Capital, Job History, and Language Factors on Job Seniority with a Large-scale Analysis of Resumes Open
As job markets worldwide have become more competitive and applicant selection criteria have become more opaque, and different (and sometimes contradictory) information and advice is available for job seekers wishing to progress in their ca…
View article: Quantifying the Impact of Human Capital, Job History, and Language Factors on Job Seniority with a Large-scale Analysis of Resumes.
Quantifying the Impact of Human Capital, Job History, and Language Factors on Job Seniority with a Large-scale Analysis of Resumes. Open
As job markets worldwide have become more competitive and applicant selection criteria have become more opaque, and different (and sometimes contradictory) information and advice is available for job seekers wishing to progress in their ca…
View article: SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models Open
Skeleton-based human action recognition technologies are increasingly used in video-based applications, such as home robotics, healthcare on the aging population, and surveillance. However, such models are vulnerable to adversarial attacks…
View article: A Comparative Analysis of Industry Human-AI Interaction Guidelines
A Comparative Analysis of Industry Human-AI Interaction Guidelines Open
With the recent release of AI interaction guidelines from Apple, Google, and Microsoft, there is clearly interest in understanding the best practices in human-AI interaction. However, industry standards are not determined by a single compa…
View article: A Comparative Analysis of Industry Human-AI Interaction Guidelines
A Comparative Analysis of Industry Human-AI Interaction Guidelines Open
With the recent release of AI interaction guidelines from Apple, Google, and Microsoft, there is clearly interest in understanding the best practices in human-AI interaction. However, industry standards are not determined by a single compa…
View article: CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization Open
Deep learning's great success motivates many practitioners and students to learn about this exciting technology. However, it is often challenging for beginners to take their first step due to the complexity of understanding and applying de…
View article: Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks Open
Deep neural networks (DNNs) are now commonly used in many domains. However, they are vulnerable to adversarial attacks: carefully crafted perturbations on data inputs that can fool a model into making incorrect predictions. Despite signifi…
View article: Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning
Massif: Interactive Interpretation of Adversarial Attacks on Deep Learning Open
Deep neural networks (DNNs) are increasingly powering high-stakes applications such as autonomous cars and healthcare; however, DNNs are often treated as "black boxes" in such applications. Recent research has also revealed that DNNs are h…
View article: Massif: Interactive Interpretation of Adversarial Attacks on Deep\n Learning
Massif: Interactive Interpretation of Adversarial Attacks on Deep\n Learning Open
Deep neural networks (DNNs) are increasingly powering high-stakes\napplications such as autonomous cars and healthcare; however, DNNs are often\ntreated as "black boxes" in such applications. Recent research has also\nrevealed that DNNs ar…
View article: Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations Open
Deep learning is increasingly used in decision-making tasks. However, understanding how neural networks produce final predictions remains a fundamental challenge. Existing work on interpreting neural network predictions for images often fo…
View article: NeuralDivergence: Exploring and Understanding Neural Networks by Comparing Activation Distributions
NeuralDivergence: Exploring and Understanding Neural Networks by Comparing Activation Distributions Open
As deep neural networks are increasingly used in solving high-stake problems, there is a pressing need to understand their internal decision mechanisms. Visualization has helped address this problem by assisting with interpreting complex d…
View article: UniWalk: Explainable and Accurate Recommendation for Rating and Network Data
UniWalk: Explainable and Accurate Recommendation for Rating and Network Data Open
How can we leverage social network data and observed ratings to correctly recommend proper items and provide a persuasive explanation for the recommendations? Many online services provide social networks among users, and it is crucial to u…
View article: A Comparative Study of Matrix Factorization and Random Walk with Restart in Recommender Systems
A Comparative Study of Matrix Factorization and Random Walk with Restart in Recommender Systems Open
Between matrix factorization or Random Walk with Restart (RWR), which method works better for recommender systems? Which method handles explicit or implicit feedback data better? Does additional information help recommendation? Recommender…