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arXiv · 2404.01182

A Neuro-Symbolic Approach to Monitoring Salt Content in Food

Anuja Tayal·Barbara Di Eugenio·Devika Salunke·Andrew D. Boyd·Carolyn A Dickens·Eulalia P Abril·Olga Garcia-Bedoya·Paula G Allen-Meares
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Abstract

We propose a dialogue system that enables heart failure patients to inquire about salt content in foods and help them monitor and reduce salt intake. Addressing the lack of specific datasets for food-based salt content inquiries, we develop a template-based conversational dataset. The dataset is structured to ask clarification questions to identify food items and their salt content. Our findings indicate that while fine-tuning transformer-based models on the dataset yields limited performance, the integration of Neuro-Symbolic Rules significantly enhances the system's performance. Our experiments show that by integrating neuro-symbolic rules, our system achieves an improvement in joint goal accuracy of over 20% across different data sizes compared to naively fine-tuning transformer-based models.

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Anuja Tayal, Barbara Di Eugenio, Devika Salunke, Andrew D. Boyd, Carolyn A Dickens, Eulalia P Abril, Olga Garcia-Bedoya, Paula G Allen-Meares. 2024-04-01. A Neuro-Symbolic Approach to Monitoring Salt Content in Food. https://arxiv.org/abs/2404.01182

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