Large Language Models (LLMs) have shown remarkable success in supporting a wide range of knowledge-intensive tasks. In specialized domains, there is growing interest in leveraging LLMs to assist subject matter experts with domain-specific challenges. However, deploying LLMs as SaaS solutions raises data privacy concerns, while many open-source models demand significant computational resources for effective domain adaptation and deployment. A promising alternative is to develop smaller, domain-sp
Building Domain-Specific Small Language Models via Guided Data Generation
Aman Kumar·Chetan Gupta·Lasitha Vidyaratne·Xian Yeow Lee·Dipanjan Ghosh·Ekant Muljibhai Amin·Yuta Koreeda·Ahmed Farahat
