activity
20242026
most citedLLM-Assisted Visual Analytics: Opportunities and Challenges

7 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2026

InSight: A Benchmark for Agentic Claim Verification in Interactive Visualizations

Maeve Hutchinson, Syed Mahbubul Huq, Mohammad Albinhassan +3

Vision Language Models have demonstrated remarkable proficiency in interpreting static visual artifacts, but modern data analysis is inherently dynamic, requiring the active interr…

cs.CV2026

Attention-Guided Saliency Maps for Interpreting Visualization Literacy in VLMs

Maeve Hutchinson, Abderrahmane Wassim Mehdaoui, Pranava Madhyastha

Understanding how vision-language models (VLMs) interpret data visualizations remains an open problem, and is increasingly important as these models are used for analytical tasks w…

cs.CL2025

Chart Question Answering from Real-World Analytical Narratives

Maeve Hutchinson, Radu Jianu, Aidan Slingsby +2

We present a new dataset for chart question answering (CQA) constructed from visualization notebooks. The dataset features real-world, multi-view charts paired with natural languag…

cs.HC2025

Capturing Visualization Design Rationale

Maeve Hutchinson, Radu Jianu, Aidan Slingsby +2

Prior natural language datasets for data visualization have focused on tasks such as visualization literacy assessment, insight generation, and visualization generation from natura…

cs.HC2024★ 7 cited

LLM-Assisted Visual Analytics: Opportunities and Challenges

Maeve Hutchinson, Radu Jianu, Aidan Slingsby +1

We explore the integration of large language models (LLMs) into visual analytics (VA) systems to transform their capabilities through intuitive natural language interactions. We su…

cs.LG2024

The Misclassification Likelihood Matrix: Some Classes Are More Likely To Be Misclassified Than Others

Daniel Sikar, Artur Garcez, Robin Bloomfield +6

This study introduces the Misclassification Likelihood Matrix (MLM) as a novel tool for quantifying the reliability of neural network predictions under distribution shifts. The MLM…