69 citations · 350 across the 44 of their papers we have counts for
45 papers
Point, Revise, Review: Grounded Agentic Analysis in Reactive Notebooks with marimo-lens
Péter Ferenc Gyarmati, Trevor Manz, Dominik Moritz +1
In a computational notebook, a human can point to a rendered result and ask about "this," while an agent acts through cells, dependencies, and runtime state. When what the human se…
Teaching Geometric Proof with Tech: Pitfalls and Possibilities
Hwei-Shin Harriman, Wode Ni, Yuchen Jin +2
Geometric proof is a foundational yet challenging topic in mathematics, requiring students to integrate visual, logical, and notational skills. While technology has enhanced learni…
Skeleton: Visual Authoring of Non-visual Data Experiences
Frank Elavsky, Chieri Nnadozie, Lucas Nadolskis +2
When sighted practitioners author accessible data visualizations, they build navigation structures (the nodes, edges, and input bindings that govern how assistive technologies trav…
VACP: Visual Analytics Context Protocol
Tobias Stähle, Péter Ferenc Gyarmati, Thilo Spinner +3
The rise of AI agents introduces a fundamental shift in Visual Analytics (VA), in which agents act as a new user group. Current agentic approaches - based on computer vision and ra…
Human-Data Interaction, Exploration, and Visualization in the AI Era: Challenges and Opportunities
Jean-Daniel Fekete, Yifan Hu, Dominik Moritz +8
The rapid advancement of AI is transforming human-centered systems, with profound implications for human-AI interaction, human-data interaction, and visual analytics. In the AI era…
Structured Visualization Design Knowledge for Grounding Generative Reasoning and Situated Feedback
Péter Ferenc Gyarmati, Dominik Moritz, Torsten Möller +1
Automated visualization design navigates a tension between symbolic systems and generative models. Constraint solvers enforce structural and perceptual validity, but the rules they…
Semantic Regexes: Auto-Interpreting LLM Features with a Structured Language
Angie Boggust, Donghao Ren, Yannick Assogba +3
Automated interpretability aims to translate large language model (LLM) features into human understandable descriptions. However, natural language feature descriptions can be vague…
A Composable Agentic System for Automated Visual Data Reporting
Péter Ferenc Gyarmati, Dominik Moritz, Torsten Möller +1
To address the brittleness of monolithic AI agents, our prototype for automated visual data reporting explores a Human-AI Partnership model. Its hybrid, multi-agent architecture st…
Apple Intelligence Foundation Language Models: Tech Report 2025
Ethan Li, Anders Boesen Lindbo Larsen, Chen Zhang +395
We introduce two multilingual, multimodal foundation language models that power Apple Intelligence features across Apple devices and services: i a 3B-parameter on-device model opti…
EncQA: Benchmarking Vision-Language Models on Visual Encodings for Charts
Kushin Mukherjee, Donghao Ren, Dominik Moritz +1
Multimodal vision-language models (VLMs) continue to achieve ever-improving scores on chart understanding benchmarks. Yet, we find that this progress does not fully capture the bre…
Mosaic Selections: Managing and Optimizing User Selections for Scalable Data Visualization Systems
Jeffrey Heer, Dominik Moritz, Ron Pechuk
Though powerful tools for analysis and communication, interactive visualizations often fail to support real-time interaction with large datasets with millions or more records. To h…
A Scalable Approach to Clustering Embedding Projections
Donghao Ren, Fred Hohman, Dominik Moritz
Interactive visualization of embedding projections is a useful technique for understanding data and evaluating machine learning models. Labeling data within these visualizations is…
Embedding Atlas: Low-Friction, Interactive Embedding Visualization
Donghao Ren, Fred Hohman, Halden Lin +1
Embedding projections are popular for visualizing large datasets and models. However, people often encounter "friction" when using embedding visualization tools: (1) barriers to ad…
Texture: Structured Exploration of Text Datasets
Will Epperson, Arpit Mathur, Adam Perer +1
Exploratory analysis of a text corpus is essential for assessing data quality and developing meaningful hypotheses. Text analysis relies on understanding documents through structur…
InterLink: Linking Text with Code and Output in Computational Notebooks
Yanna Lin, Leni Yang, Haotian Li +2
Computational notebooks, widely used for ad-hoc analysis and often shared with others, can be difficult to understand because the standard linear layout is not optimized for readin…
Towards softerware: Enabling personalization of interactive data representations for users with disabilities
Frank Elavsky, Marita Vindedal, Ted Gies +3
Accessible design for some may still produce barriers for others. This tension, called access friction, creates challenges for both designers and end-users with disabilities. To ad…
Exploring Empty Spaces: Human-in-the-Loop Data Augmentation
Catherine Yeh, Donghao Ren, Yannick Assogba +2
Data augmentation is crucial to make machine learning models more robust and safe. However, augmenting data can be challenging as it requires generating diverse data points to rigo…
Policy Maps: Tools for Guiding the Unbounded Space of LLM Behaviors
Michelle S. Lam, Fred Hohman, Dominik Moritz +3
AI policy sets boundaries on acceptable behavior for AI models, but this is challenging in the context of large language models (LLMs): how do you ensure coverage over a vast behav…
Opening the Black Box of 3D Reconstruction Error Analysis with VECTOR
Racquel Fygenson, Kazi Jawad, Isabel Li +5
Reconstruction of 3D scenes from 2D images is a technical challenge that impacts domains from Earth and planetary sciences and space exploration to augmented and virtual reality. T…
Compress and Compare: Interactively Evaluating Efficiency and Behavior Across ML Model Compression Experiments
Angie Boggust, Venkatesh Sivaraman, Yannick Assogba +3
To deploy machine learning models on-device, practitioners use compression algorithms to shrink and speed up models while maintaining their high-quality output. A critical aspect o…
Talaria: Interactively Optimizing Machine Learning Models for Efficient Inference
Fred Hohman, Chaoqun Wang, Jinmook Lee +7
On-device machine learning (ML) moves computation from the cloud to personal devices, protecting user privacy and enabling intelligent user experiences. However, fitting models on…
Optimizing Dataflow Systems for Scalable Interactive Visualization
Junran Yang, Hyekang Kevin Joo, Sai Yerramreddy +2
Supporting the interactive exploration of large datasets is a popular and challenging use case for data management systems. Traditionally, the interface and the back-end system are…
Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiences
Fred Hohman, Mary Beth Kery, Donghao Ren +1
On-device machine learning (ML) promises to improve the privacy, responsiveness, and proliferation of new, intelligent user experiences by moving ML computation onto everyday perso…
Draco 2: An Extensible Platform to Model Visualization Design
Junran Yang, Péter Ferenc Gyarmati, Zehua Zeng +1
Draco introduced a constraint-based framework to model visualization design in an extensible and testable form. It provides a way to abstract design guidelines from theoretical and…