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2024 EMNLP EMNLP 2024

Assisting Breastfeeding and Maternity Experts in Responding to User Queries with an AI-in-the-loop Approach

AbstractBreastfeeding and Maternity experts are a scarce resource and engaging in a conversation with mothers on such a sensitive topic is a time-consuming effort. We present our journey and rationale in assisting experts to answer queries about Breastfeeding and Maternity topics from users, mainly mothers. We started by developing a RAG approach to response generation where the generated response is made available to the expert who has the option to draft an answer using the generated text or to answer from scratch. This was the start of an ongoing effort to develop a pipeline of AI/NLP-based functionalities to help experts understand user queries and craft their responses.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Healthcare & Medicine and Natural Language Processing
📈 Trend Setter - Retrieval-Augmented Generation

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