On The Persona-based Summarization of Domain-Specific Documents
Ankan Mullick, Sombit Bose, Rounak Saha, Ayan Bhowmick, Pawan Goyal, Niloy Ganguly, Prasenjit Dey, Ravi Kokku
Abstract
In an ever-expanding world of domain-specific knowledge, the increasing complexity of consuming, and storing information necessitates the generation of summaries from large information repositories. However, every persona of a domain has different requirements of information and hence their summarization. For example, in the healthcare domain, a persona-based (such as Doctor, Nurse, Patient etc.) approach is imperative to deliver targeted medical information efficiently. Persona-based summarization of domain-specific information by humans is a high cognitive load task and is generally not preferred. The summaries generated by two different humans have high variability and do not scale in cost and subject matter expertise as domains and personas grow. Further, AI-generated summaries using generic Large Language Models (LLMs) may not necessarily offer satisfactory accuracy for different domains unless they have been specifically trained on domain-specific data and can also be very expensive to use in day-to-day operations. Our contribution in this paper is two-fold: 1) We present an approach to efficiently fine-tune a domain-specific small foundation LLM using a healthcare corpus and also show that we can effectively evaluate the summarization quality using AI-based critiquing. 2) We further show that AI-based critiquing has good concordance with Human-based critiquing of the summaries. Hence, such AI-based pipelines to generate domain-specific persona-based summaries can be easily scaled to other domains such as legal, enterprise documents, education etc. in a very efficient and cost-effective manner.- Anthology ID:
- 2024.findings-acl.849
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2024
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 14291–14307
- Language:
- URL:
- https://aclanthology.org/2024.findings-acl.849
- DOI:
- 10.18653/v1/2024.findings-acl.849
- Cite (ACL):
- Ankan Mullick, Sombit Bose, Rounak Saha, Ayan Bhowmick, Pawan Goyal, Niloy Ganguly, Prasenjit Dey, and Ravi Kokku. 2024. On The Persona-based Summarization of Domain-Specific Documents. In Findings of the Association for Computational Linguistics: ACL 2024, pages 14291–14307, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- On The Persona-based Summarization of Domain-Specific Documents (Mullick et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/autopr/2024.findings-acl.849.pdf