Severity-Aware Curriculum Learning with Multi-Model Response Selection for Medical Text Generation
Telehealth systems have become increasingly important for delivering accessible and timely medical information. Existing large language models often struggle to provide consistent and contextually appropriate medical responses across varying levels of case severity. This limitation highlights the need for models that can effectively adapt to the progressive complexity in medical queries. To address this challenge, we introduce a severity-aware multi-model framework that integrates curriculum training strategy with relevance-based response selection. The proposed framework employs a three-stage curriculum learning strategy, where each model is trained sequentially on mild, moderate, and cr...
| Authors | Ahmed Alansary, Molham Mohamed, Ali Hamdi |
|---|---|
| Primary category | cs.AI |
| Published | 3 June 2026 |
| Last updated at source | 13 July 2026 |
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