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Caring for a child with cancer involves navigating through complex medical information, often delivered through lengthy handbooks and consultations with healthcare providers. Overnight, parents are expected to become an expert on a domain which they knew noth- ing about. Conversational UIs, powered by Large Language Models (LLMs) and validated information sources, could play a key role in supporting caregivers. In this paper, we investigate the usability, acceptance, and perceived utility of an LLM-based conversational AI tool for pediatric cancer caregiving, grounded in the Children’s Oncology Group Family Handbook–the leading resource in pe- diatric oncology care. We employed a mixed-methods approach, interviewing and surveying 12 caregivers as they engaged with a functional prototype. We offer insights into caregiver’s needs and expectations from AI-driven tools, and design guidelines for devel- oping safer, more personalized, and supportive AI interventions for pediatric cancer care.
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This content will become publicly available on April 25, 2026
An Investigation of Interaction and Information Needs for Protocol Reverse Engineering Automation
Protocol reverse engineering (ProtocolREing) consists of taking streams of network data and inferring the communication protocol. ProtocolREing is critical task in malware and system security analysis. Several ProtocolREing automation tools have been developed, however, in practice, they are not used because they offer limited interaction. Instead, reverse engineers (ProtocolREs) perform this task manually or use less complex visualization tools. To give ProtocolREs the power of more complex automation, we must first understand ProtocolREs processes and information and interaction needs to design better interfaces. We interviewed 16 ProtocolREs, presenting a paper prototype ProtocolREing automation interface, and ask them to discuss their approach to ProtocolREing while using the tool and suggest missing information and interactions. We designed our prototype based on existing ProtocolREing tool features and prior reverse engineering research’s usability guidelines. We found ProtocolREs follow a flexible, hypothesis-driven process and identified multiple information and interaction needs when validating the automation’s inferences. We provide suggestions for future interaction design.
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- Award ID(s):
- 1955805
- PAR ID:
- 10618333
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400713941
- Page Range / eLocation ID:
- 1 to 21
- Format(s):
- Medium: X
- Location:
- Yokohama Japan
- Sponsoring Org:
- National Science Foundation
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