Proceedings of the CHI Conference on Human Factors in Computing Systems 2024
DOI: 10.1145/3613904.3642450
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Memoro: Using Large Language Models to Realize a Concise Interface for Real-Time Memory Augmentation

Wazeer Deen Zulfikar,
Samantha Chan,
Pattie Maes

Abstract: People have to remember an ever-expanding volume of information. Wearables that use information capture and retrieval for memory augmentation can help but can be disruptive and cumbersome in real-world tasks, such as in social settings. To address this, we developed Memoro, a wearable audio-based memory assistant with a concise user interface. Memoro uses a large language model (LLM) to infer the user's memory needs in a conversational context, semantically search memories, and present minimal suggestions. The… Show more

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