MuDoC: An Interactive Multimodal Document-grounded Conversational AI System

Multimodal AI is an important step towards building effective tools to leverage multiple modalities in human-AI communication. Building a multimodal document-grounded AI system to interact with long documents remains a challenge. Our work aims to fill the research gap of directly leveraging grounded visuals from documents alongside textual content in documents for response generation. We present an interactive conversational AI agent 'MuDoC' based on GPT-4o to generate document-grounded responses with interleaved text and figures. MuDoC's intelligent textbook interface promotes trustworthiness and enables verification of system responses by allowing instant navigation to source text and figures in the documents. We also discuss qualitative observations based on MuDoC responses highlighting its strengths and limitations.

Authors

Institutions

Publication Details

Journal
Proceedings of the AAAI Symposium Series
Published
2025-05-28
DOI
https://doi.org/10.1609/aaaiss.v5i1.35619
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MuDoC: An Interactive Multimodal Document-grounded Conversational AI System

Ashok K. Goel, Karan Taneja
Proceedings of the AAAI Symposium Series
Natural Language Processing Techniques
article

MuDoC: An Interactive Multimodal Document-grounded Conversational AI System

Ashok K. Goel, Karan Taneja
article en

Abstract

Multimodal AI is an important step towards building effective tools to leverage multiple modalities in human-AI communication. Building a multimodal document-grounded AI system to interact with long documents remains a challenge. Our work aims to fill the research gap of directly leveraging grounded visuals from documents alongside textual content in documents for response generation. We present an interactive conversational AI agent 'MuDoC' based on GPT-4o to generate document-grounded responses with interleaved text and figures. MuDoC's intelligent textbook interface promotes trustworthiness and enables verification of system responses by allowing instant navigation to source text and figures in the documents. We also discuss qualitative observations based on MuDoC responses highlighting its strengths and limitations.

Proceedings of the AAAI Symposium SeriesVol. 5(1)
Georgia Institute of Technology (US)
National Science Foundation, Bill and Melinda Gates Foundation
Openalex Percentile: Top 94%
Natural Language Processing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.