MuDoC: An Interactive Multimodal Document-grounded Conversational AI System
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Abstract (arXiv)
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.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 13 of its 19 references that are in the map. First posted on arXiv 14 Feb 2025.
Builds on
13 of 19 references.
References · 13
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- 2024Jill Watson: A Virtual Teaching Assistant powered by ChatGPTcited by 24
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.