Retrieval-Augmented Technical Document QA
Published:
Development of a retrieval-augmented workflow for parsing technical documents, finding relevant passages with vector search, and generating grounded answers with language models.
Liu Hengjie
Ph.D. student at Kyushu University working on AI safety, formal verification, and certified robustness of Transformer models.
- Fukuoka, Japan
- Kyushu University
- Google Scholar
- ORCID
- GitHub