Paper Detail
Mohammad Abolnejadian, Matthew Brehmer
Missing institutional context during meetings can impede effective participation. Retrieving relevant information, often scattered across heterogeneous internal and external sources, requires costly task-switching that disrupts both individual focus and collective conversational flow, particularly detrimental during cognitively demanding tasks such as decision-making. We introduce InsightToast, a mixed-initiative application that monitors verbal discourse in real time, identifies topics and informational needs as they emerge, and proactively retrieves relevant information through a multi-agent large language model (LLM)-based pipeline integrating retrieval-augmented generation (RAG) to produce source-grounded insights as succinct text and glanceable interactive charts, delivered through a peripheral interface as ephemeral toasts in the conversation's side channel. To demonstrate the potential for yielding serendipitous insights, we showcase a usage scenario involving a knowledge base of legislative documents as the meeting's context. We then report on a comparative study (N=16), in which participants arrived at informed policy decisions while maintaining natural conversation flow.
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@article{abolnejadian2026insighttoast,
title = {InsightToast: Proactive Information Retrieval \& Glanceable Visualization in the Side Channel of Data-Rich Meetings},
author = {Mohammad Abolnejadian and Matthew Brehmer},
year = {2026},
abstract = {Missing institutional context during meetings can impede effective participation. Retrieving relevant information, often scattered across heterogeneous internal and external sources, requires costly task-switching that disrupts both individual focus and collective conversational flow, particularly detrimental during cognitively demanding tasks such as decision-making. We introduce InsightToast, a mixed-initiative application that monitors verbal discourse in real time, identifies topics and info},
url = {https://arxiv.org/abs/2608.31115},
keywords = {cs.HC, cs.IR},
eprint = {2608.31115},
archiveprefix = {arXiv},
}
{}