4 papers
VisDoM: Multi-Document QA with Visually Rich Elements Using Multimodal Retrieval-Augmented Generation
Manan Suri, Puneet Mathur, Franck Dernoncourt +3
Understanding information from a collection of multiple documents, particularly those with visually rich elements, is important for document-grounded question answering. This paper…
ChartCitor: Multi-Agent Framework for Fine-Grained Chart Visual Attribution
Kanika Goswami, Puneet Mathur, Ryan Rossi +1
Large Language Models (LLMs) can perform chart question-answering tasks but often generate unverified hallucinated responses. Existing answer attribution methods struggle to ground…
PlotGen: Multi-Agent LLM-based Scientific Data Visualization via Multimodal Feedback
Kanika Goswami, Puneet Mathur, Ryan Rossi +1
Scientific data visualization is pivotal for transforming raw data into comprehensible visual representations, enabling pattern recognition, forecasting, and the presentation of da…
PlotEdit: Natural Language-Driven Accessible Chart Editing in PDFs via Multimodal LLM Agents
Kanika Goswami, Puneet Mathur, Ryan Rossi +1
Chart visualizations, while essential for data interpretation and communication, are predominantly accessible only as images in PDFs, lacking source data tables and stylistic infor…