1. A Neuro-Symbolic Approach to Monitoring Salt Content in Food
- Author
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Tayal, Anuja, Di Eugenio, Barbara, Salunke, Devika, Boyd, Andrew D., Dickens, Carolyn A, Abril, Eulalia P, Garcia-Bedoya, Olga, and Allen-Meares, Paula G
- Subjects
Computer Science - Computation and Language ,Computer Science - Symbolic Computation - 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., Comment: Accepted in CL4Health workshop in LREC-COLING'24
- Published
- 2024