Supporting The Many Lives of Personal Data with Rebite: LLM-Powered Goal-Directed Framing in Food Journaling

2026-08-21

AI Summary

为了解决个人健康追踪系统难以适应用户目标变化的问题，本文提出了一种基于LLM的目标导向框架方法，并通过Rebite食物日记系统进行了实现和验证。

Abstract

People's health and tracking goals frequently change, but most personal informatics systems struggle to adapt, leading people to abandon their data and start over. We propose goal-directed framing, an approach that repositions goals within personal informatics systems. Instead of fixing the meaning of data at capture time, the approach frames the collected data through the current goal and reframes it whenever the goal changes. We realize this in Rebite, a photo-based food journaling system that uses LLMs to read unstructured meal photos and produce goal-directed feedback. In a one-week deployment with 21 participants managing multiple dietary goals, we find that goal-directed framing shaped how participants engaged with their goals. Translating a goal into metrics helped them see what it meant in practice, confirming existing priorities, surfacing what they overlooked, and revealing where the metrics fell short. When goals changed, seeing past meals reframed under the new goal exposed overlaps and conflicts, prompting participants to negotiate trade-offs and refine priorities. We discuss how goal-directed framing both supports and complicates reflection as goals change, and offer design implications for personal informatics systems to support evolving goals.

Problem

• personal informatics systems
• changing goals
• data abandonment
• goal-directed framing
• food journaling

Innovation

• goal-directed framing
• LLM-powered feedback
• personal informatics systems
• evolving goals