Minsuk Kahng 강민석

Preprints

• From Seed to Harvest: Augmenting Human Creativity with AI for Red-teaming Text-to-Image Models
  Jessica Quaye, Charvi Rastogi, Alicia Parrish, Oana Inel, Minsuk Kahng, Lora Aroyo, and Vijay Janapa Reddi
• SafePath: Preventing Harmful Reasoning in Chain-of-Thought via Early Alignment
  Wonje Jeung, Sangyeon Yoon, Minsuk Kahng, and Albert No
• Multi-turn Evaluation of Anthropomorphic Behaviours in Large Language Models
  Lujain Ibrahim, Canfer Akbulut, Rasmi Elasmar, Charvi Rastogi, Minsuk Kahng, Meredith Ringel Morris, Kevin R McKee, Verena Rieser, Murray Shanahan, and Laura Weidinger
• Gemma 2: Improving Open Language Models at a Practical Size
  Google DeepMind Gemma Team
• Interactive Prompt Debugging with Sequence Salience
  Ian Tenney, Ryan Mullins, Bin Du, Shree Pandya, Minsuk Kahng, and Lucas Dixon

Publications

• LLM Adoption in Data Curation Workflows: Industry Practices and Insights
  Crystal Qian, Michael Xieyang Liu, Emily Reif, Grady Simon, Nada Hussein, Nathan Clement, James Wexler, Carrie J. Cai, Michael Terry, and Minsuk Kahng
  ACM CHI conference on Human Factors in Computing Systems (CHI'25), Late Breaking Work Poster, 2025.
  DOI
• From Perception to Decision: Assessing the Role of Chart Types Affordances in High-Level Decision Tasks
  Yixuan Li, Emery D. Berger, Minsuk Kahng, and Cindy Xiong Bearfield
  IEEE Conference on Visualization and Visual Analytics (VIS'25), Short, 2025.
  arXiv PDF
• LLM Attributor: Interactive Visual Attribution for LLM Generation
  Seongmin Lee, Zijie J Wang, Aishwarya Chakravarthy, Alec Helbling, ShengYun Peng, Mansi Phute, Duen Horng Chau, and Minsuk Kahng
  Proceedings of the AAAI Conference on Artificial Intelligence (AAAI'25), Demo, 2025.
  DOI
• 
  LLM Comparator: Interactive Analysis of Side-by-Side Evaluation of Large Language Models
  Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, and Lucas Dixon
  IEEE Transactions on Visualization and Computer Graphics (VIS'24), 2025.
  DOI PDF Blog Code
  Deployed on Google's LLM Evaluation Platforms
  Featured at Google I/O on Gemini Open Models and Responsible AI Toolkit
• Lexically-Constrained Automated Prompt Augmentation: A Case Study using Adversarial T2I Data
  Jessica Quaye, Alicia Parrish, Oana Inel, Minsuk Kahng, Charvi Rastogi, Hannah Rose Kirk, Jess Tsang, Nathan L Clement, Rafael Mosquera, Juan Manuel Ciro, Vijay Janapa Reddi, and Lora Aroyo
  Safe Generative AI Workshop @ NeurIPS, 2024.
  PDF
• 
  Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation
  Jessica Quaye, Alicia Parrish, Oana Inel, Charvi Rastogi, Hannah Rose Kirk, Minsuk Kahng, Erin van Liemt, Max Bartolo, Jess Tsang, Justin White, Nathan Clement, Rafael Mosquera, Juan Ciro, Vijay Janapa Reddi, and Lora Aroyo
  ACM Conference on Fairness, Accountability, and Transparency (FAccT'24), 2024.
  arXiv PDF Blog
• 
  Automatic Histograms: Leveraging Language Models for Text Dataset Exploration
  Emily Reif, Crystal Qian, James Wexler, and Minsuk Kahng
  ACM CHI conference on Human Factors in Computing Systems (CHI'24), Late Breaking Work Poster, 2024.
  DOI arXiv PDF Code
• Understanding the Dataset Practitioners Behind Large Language Model Development
  Crystal Qian, Emily Reif, and Minsuk Kahng
  ACM CHI conference on Human Factors in Computing Systems (CHI'24), Late Breaking Work Poster, 2024.
  DOI arXiv PDF
• 
  LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models
  Minsuk Kahng, Ian Tenney, Mahima Pushkarna, Michael Xieyang Liu, James Wexler, Emily Reif, Krystal Kallarackal, Minsuk Chang, Michael Terry, and Lucas Dixon
  ACM CHI conference on Human Factors in Computing Systems (CHI'24), Late Breaking Work Poster, 2024.
  DOI arXiv PDF Blog Code
  Deployed on Google's LLM Evaluation Platforms
  Featured at Google I/O on Gemini Open Models and Responsible AI Toolkit
• 
  VLSlice: Interactive Vision-and-Language Slice Discovery
  Eric Slyman, Minsuk Kahng, Stefan Lee
  International Conference on Computer Vision (ICCV'23), 2023.
  PDF Website
• 
  Visualizing Linguistic Diversity of Text Datasets Synthesized by Large Language Models
  Emily Reif, Minsuk Kahng, Savvas Petridis
  IEEE Visualization Conference (VIS'23), Short, 2023.
  PDF
• 
  VIVA: Visual Exploration and Analysis of Videos with Interactive Annotation
  Anita Ruangrotsakun, Dayeon Oh, Thuy-Vy Nguyen, Kristina Lee, Mark Ser, Arthur Hiew, Rogers Ngo, Zeyad Shureih, Roli Khanna, Minsuk Kahng
  28th ACM International Conference on Intelligent User Interfaces (IUI'23), Demo, 2023.
  DOI PDF
• 
  DendroMap: Visual Exploration of Large-Scale Image Datasets for Machine Learning with Treemaps
  Donald Bertucci, Md Montaser Hamid, Yashwanthi Anand, Anita Ruangrotsakun, Delyar Tabatabai, Melissa Perez, Minsuk Kahng
  IEEE Transactions on Visualization and Computer Graphics, 29(1) (VIS'22), 2023.
  DOI PDF Twitter Post Demo
• Beyond Value: CheckList for Testing Inferences in Planning-Based RL
  Kin-Ho Lam, Delyar Tabatabai, Jed Irvine, Donald Bertucci, Anita Ruangrotsakun, Minsuk Kahng, Alan Fern
  32nd International Conference on Automated Planning and Scheduling (ICAPS'22), 2022.
  AAAI PDF
• 
  FitVid: Responsive and Flexible Video Content Adaptation
  Jeongyeon Kim, Yubin Choi, Minsuk Kahng, Juho Kim
  ACM CHI Conference on Human Factors in Computing Systems (CHI'22), 2022.
  DOI PDF
• 
  Finding AI's Faults with AAR/AI: An Empirical Study
  Roli Khanna, Jonathan Dodge, Andrew Anderson, Rupika Dikkala, Jed Irvine, Zeyad Shureih, Kin-Ho Lam, Caleb R. Matthews, Zhengxian Lin, Minsuk Kahng, Alan Fern, Margaret Burnett
  ACM Transactions on Interactive Intelligent Systems, 12(1) (TiiS), 2022.
  DOI PDF
• 
  One Explanation is Not Enough: Structured Attention Graphs for Image Classification
  Vivswan Shitole, Li Fuxin, Minsuk Kahng, Prasad Tadepalli, Alan Fern
  35th Conference on Neural Information Processing Systems (NeurIPS'21), 2021.
  PDF arXiv
• 
  Contrastive Identification of Covariate Shift in Image Data
  Matthew L. Olson, Thuy-Vy Nguyen, Gaurav Dixit, Neale Ratzlaff, Weng-Keen Wong, Minsuk Kahng
  IEEE Visualization Conference (VIS'21), Short, 2021.
  DOI PDF
• 
  "Why did my AI agent lose?": Visual Analytics for Scaling Up After-Action Review
  Delyar Tabatabai, Anita Ruangrotsakun, Jed Irvine, Jonathan Dodge, Zeyad Shureih, Kin-Ho Lam, Margaret Burnett, Alan Fern, Minsuk Kahng
  IEEE Visualization Conference (VIS'21), Short, 2021.
  DOI PDF
• Backprop Explainer: Interactive Explanation of Backpropagation in Neural Network Training
  Donald R. Bertucci, Minsuk Kahng
  4th Workshop on Visualization for AI Explainability (VISxAI at VIS'21), 2021.
  Interactive Article
• From Heatmaps to Structural Explanations of Image Classifiers
  Li Fuxin, Zhongang Qi, Saeed Khorram, Vivswan Shitole, Prasad Tadepalli, Minsuk Kahng, Alan Fern
  Applied AI Letters, 2021.
  DOI
• From "No Clear Winner" to an Effective XAI Process: An Empirical Journey
  Jonathan Dodge, Andrew Anderson, Roli Khanna, Jed Irvine, Rupika Dikkala, Kin-Ho Lam, Delyar Tabatabai, Anita Ruangrotsakun, Zeyad Shureih, Minsuk Kahng, Alan Fern, Margaret Burnett
  Applied AI Letters, 2021.
  DOI PDF
• Doing Remote Controlled Studies with Humans: Tales from the COVID Trenches
  Rupika Dikkala, Roli Khanna, Caleb Matthews, Jonathan Dodge, Sai Raja, Catherine Hu, Jed Irvine, Zeyad Shureih, Kin-Ho Lam, Andrew Anderson, Minsuk Kahng, Alan Fern, Margaret Burnett
  ACM/IEEE 14th International Conference on Cooperative and Human Aspects of Software Engineering (CHASE'21), 2021.
  DOI PDF
• 
  CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
  Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, Duen Horng (Polo) Chau
  IEEE Transactions on Visualization and Computer Graphics (VIS'20), 2020.
  DOI PDF Demo Video Code
• How Does Visualization Help People Learn Deep Learning? Evaluation of GAN Lab with Observational Study and Log Analysis
  Minsuk Kahng, Duen Horng (Polo) Chau
  IEEE Visualization Conference (VIS'20), Short, 2020.
  PDF
• Identifying Reasoning Flaws in Planning-Based RL Using Tree Explanations
  Kin-Ho Lam, Zhengxian Lin, Jed Irvine, Jonathan Dodge, Zeyad T Shureih, Roli Khanna, Minsuk Kahng, Alan Fern
  IJCAI-PRICAI 2020 Workshop on Explainable Artificial Intelligence (XAI), 2020.
  PDF
• CNN 101: Interactive Visual Learning for Convolutional Neural Networks
  Zijie J. Wang, Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, Duen Horng (Polo) Chau
  ACM SIGCHI Conference on Human Factors in Computing Systems (CHI'20), Late Breaking Work Poster, 2020.
  PDF
• 
  FairVis: Visual Analytics for Discovering Intersectional Bias in Machine Learning
  Ángel Alexander Cabrera, Will Epperson, Fred Hohman, Minsuk Kahng, Jamie Morgenstern, Duen Horng (Polo) Chau
  IEEE Conference on Visual Analytics Science and Technology (VIS'19), 2019.
  DOI PDF arXiv Blog Code
• 
  Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
  Fred Hohman, Minsuk Kahng, Robert Pienta, Duen Horng (Polo) Chau
  IEEE Transactions on Visualization and Computer Graphics, 25(8), 2019.
  DOI PDF Website Medium
• How Does Visualization Help People Learn Deep Learning? Evaluation of GAN Lab
  Minsuk Kahng, Duen Horng (Polo) Chau
  Workshop on Evaluation of Interactive Visual Machine Learning Systems (EVIVA-ML at IEEE VIS'19), 2019.
  PDF
• Discovery of Intersectional Bias in Machine Learning Using Automatic Subgroup Generation
  Ángel Alexander Cabrera, Minsuk Kahng, Fred Hohman, Jamie Morgenstern, Duen Horng (Polo) Chau
  Debugging Machine Learning Models Workshop (at ICLR'19), 2019.
  PDF
• 
  GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
  Minsuk Kahng, Nikhil Thorat, Duen Horng (Polo) Chau, Fernanda Viégas, Martin Wattenberg
  IEEE Transactions on Visualization and Computer Graphics, 25(1) (VIS'18), 2019.
  Open sourced with Google AI
  DOI PDF Slides Code Website
• Chronodes: Interactive Multifocus Exploration of Event Sequences
  Peter J. Polack Jr., Shang-Tse Chen, Minsuk Kahng, Kaya De Barbaro, Rahul Basole, Moushumi Sharmin, Duen Horng (Polo) Chau
  ACM Transactions on Interactive Intelligent Systems (TiiS), 8(1), 2018.
  Best Paper, Honorable Mention
  DOI PDF
• 
  ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models
  Minsuk Kahng, Pierre Y. Andrews, Aditya Kalro, Duen Horng (Polo) Chau
  IEEE Transactions on Visualization and Computer Graphics, 24(1) (VIS'17), 2018.
  Deployed on Facebook ML Platform; Invited to present at SIGGRAPH'18 as a top VIS paper (4 total)
  DOI PDF Video Slides Website
• Designing a Visual Analytic System for Industry-Scale Deep Neural Network Models
  Minsuk Kahng, Pierre Y. Andrews, Aditya Kalro, Duen Horng (Polo) Chau
  Workshop on Visual Analytics for Deep Learning (VADL at IEEE VIS'17), 2017.
  A summary version of the paper presented at VIS'17 listed above.
  PDF
• FACETS: Adaptive Local Exploration of Large Graphs
  Robert Pienta, Minsuk Kahng, Zhiyuan Lin, Jilles Vreeken, Partha Talukdar, James Abello, Ganesh Parameswaran, Duen Horng (Polo) Chau
  SIAM International Conference on Data Mining (SDM'17), 2017.
  DOI PDF
• 
  Interactive Browsing and Navigation in Relational Databases
  Minsuk Kahng, Shamkant B. Navathe, John T. Stasko, Duen Horng (Polo) Chau
  Proceedings of the VLDB Endowment, 9(12) (VLDB'16), 2016.
  DOI PDF Slides
• M-Flash: Fast Billion-scale Graph Computation Using a Bimodal Block Processing Model
  Hugo Gualdron, Robson Cordeiro, Jose Rodrigues Jr., Duen Horng (Polo) Chau, Minsuk Kahng, U Kang
  European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'16), 2016.
  DOI
• mHealth Visual Discovery Dashboard
  Dezhi Fang, Fred Hohman, Peter Polack, Hillol Sarker, Minsuk Kahng, Moushumi Sharmin, Mustafa al'Absi, Duen Horng (Polo) Chau
  ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp'17), Demo, 2017.
  PDF Video
• Exploratory Visual Analytics of Mobile Health Data: Sensemaking Challenges and Opportunities
  Peter J. Polack Jr., Moushumi Sharmin, Kaya de Barbaro, Minsuk Kahng, Shang-Tse Chen, Duen Horng (Polo) Chau
  Mobile Health: Sensors, Analytic Methods, and Applications, Springer, 2017.
  DOI
• 
  Visual Exploration of Machine Learning Results using Data Cube Analysis
  Minsuk Kahng, Dezhi Fang, Duen Horng (Polo) Chau
  Workshop on Human-In-the-Loop Data Analytics (HILDA at SIGMOD'16), 2016.
  Deployed on Facebook ML Platform
  DOI PDF Slides
• STEPS: A Spatio-temporal Electric Power Systems Visualization
  Robert Pienta, Leilei Xiong, Santiago Grijalva, Duen Horng (Polo) Chau, Minsuk Kahng
  ACM International Conference on Intelligent User Interfaces (IUI'16), Poster, 2016.
  DOI
• Understanding Variations in Pediatric Asthma Care Processes in the Emergency Department using Visual Analytics
  Rahul C. Basole, Mark Braunstein, Vikas Kumar, Hyunwoo Park, Minsuk Kahng, Duen Horng (Polo) Chau, Acar Tamersoy, Daniel A. Hirsh, Nicoleta Serban, James Bost, Burton Lesnick, Beth L. Schissel, Michael Thompson
  Journal of the American Medical Informatics Association, 22(2) (Special Issue on Visual Analytics in Healthcare), 2015.
  DOI
• Constructing Compact and Effective Graphs for Recommender Systems via Node and Edge Aggregations
  Sangkeun Lee, Minsuk Kahng, and Sang-goo Lee
  Expert Systems with Applications, 42(7), 2015.
  DOI
• TimeStitch: Interactive Multi-focus Cohort Discovery and Comparison
  Peter Polack, Shang-Tse Chen, Minsuk Kahng, Moushumi Sharmin, Duen Horng (Polo) Chau
  IEEE Conference on Visual Analytics Science and Technology (VIS'15), Poster, IEEE, 2015.
  DOI PDF
• AdaptiveNav: Adaptive Discovery of Interesting and Surprising Nodes in Large Graphs
  Robert Pienta, Zhiyuan Lin, Minsuk Kahng, Jilles Vreeken, Partha P. Talukdar, James Abello, Ganesh Parameswaran, Duen Horng (Polo) Chau
  IEEE VIS Conference (VIS'15), Poster, 2015.
  PDF
• A Visual Analytics Approach to Understanding Care Process Variation and Conformance
  Rahul C. Basole, Hyunwoo Park, Mayank Gupta, Mark Braunstein, Duen Horng (Polo) Chau, Michael Thompson, Vikas Kumar, Robert Pienta, Minsuk Kahng
  Workshop on Visual Analytics in Healthcare (at VIS'15), 2015.
  DOI
• Scalable Graph Exploration and Visualization: Sensemaking Challenges and Opportunities
  Robert Pienta, James Abello, Minsuk Kahng, Duen Horng (Polo) Chau
  International Conference on Big Data and Smart Computing (Invited), 2015.
  DOI PDF
• 
  GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration
  Charles D. Stolper, Minsuk Kahng, Zhiyuan Lin, Florian Foerster, Aakash Goel, John Stasko, and Duen Horng (Polo) Chau
  IEEE Transactions on Visualization and Computer Graphics, 20(12) (InfoVis as part of VIS'14), 2014.
  DOI PDF Video
• MMap: Fast Billion-Scale Graph Computation on a PC via Memory Mappping
  Zhiyuan Lin, Minsuk Kahng, Kaeser Md. Sabrin, Duen Horng (Polo) Chau, Ho Lee, U Kang
  IEEE International Conference on Big Data, 2014.
  DOI PDF Website
• Bicentric Visualization of Pediatric Asthma Care Process Activities
  Rahul C. Basole, Hyunwoo Park, Vikas Kumar, Mark Braunstein, James Bost, Duen Horng (Polo) Chau, Minsuk Kahng
  IEEE VIS Workshop on EHR Data (at VIS'14), 2014.
  PDF
• Towards Scalable Graph Computation on Mobile Devices
  Yiqi Chen, Zhiyuan Lin, Robert Pienta, Minsuk Kahng, Duen Horng (Polo) Chau
  IEEE BigData Workshop on Scalable Machine Learning (at BigData'14), 2014.
  DOI PDF
• Exploring Clinical Care Processes Using Visual and Data Analytics: Challenges and Opportunities
  Vikas Kumar, Hyunwoo Park, Rahul C. Basole, Mark Braunstein, Minsuk Kahng, Duen Horng (Polo) Chau, Acar Tamersoy, Daniel A. Hirsh, Nicoleta Serban, James Bost, Burton Lesnick, Beth Schissel, Michael Thompson
  KDD Workshop on Data Science for Social Good (at KDD'14), 2014.
  PDF
• GLOs: Graph-Level Operations for Exploratory Network Visualization
  Charles D. Stolper, Florian Foerster, Minsuk Kahng, Zhiyuan Lin, Aakash Goel, John Stasko, and Duen Horng (Polo) Chau
  ACM SIGCHI Conference on Human Factors in Computing Systems (CHI'14), Extended Abstracts, 2014.
  DOI PDF
• PathRank: Ranking nodes on a heterogeneous graph for flexible hybrid recommender systems
  Sangkeun Lee, Sungchan Park, Minsuk Kahng, Sang-goo Lee
  Expert Systems with Applications, 40(2), 2013.
  An extended version of the paper presented at CIKM'12 listed below.
  DOI
• Exploiting Paths for Entity Search in RDF Graphs
  Minsuk Kahng, Sang-goo Lee
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'12), Poster, 2012.
  DOI PDF Poster
• PathRank: A Novel Node Ranking Measure on a Heterogeneous Graph for Recommender Systems
  Sangkeun Lee, Sungchan Park, Minsuk Kahng, Sang-goo Lee
  ACM Conference on Information and Knowledge Management (CIKM'12), 2012.
  DOI
• Ranking Objects by Following Paths in Entity-Relationship Graphs
  Minsuk Kahng, Sangkeun Lee, Sang-goo Lee
  ACM Workshop for Ph.D. Students in Information and Knowledge Management (Ph.D. Workshop at CIKM'11), 2011.
  Best Paper Award
  DOI PDF Slides
• Ranking in Context-Aware Recommender Systems
  Minsuk Kahng, Sangkeun Lee, Sang-goo Lee
  International Conference on World Wide Web (WWW'11), Poster, 2011.
  DOI PDF Poster
• Random Walk based Entity Ranking on Graph for Multidimensional Recommendation
  Sangkeun Lee, Sang-il Song, Minsuk Kahng, Dongjoo Lee, Sang-goo Lee
  ACM Conference on Recommender Systems (RecSys'11), 2011.
  DOI PDF
• Exploiting Contextual Information from Event Logs for Personalized Recommendation
  Dongjoo Lee, Sung Eun Park, Minsuk Kahng, Sangkeun Lee, Sang-goo Lee
  Computer and Information Science 2010, Studies in Computational Intelligence, Springer, 2010.
  DOI
• Si-Fi: Interactive Similar Item Finder
  Inbeom Hwang, Minsuk Kahng, Sung Eun Park, Jinwook Seo, Sang-goo Lee
  ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'10), Demo, 2010.
  DOI