Speaker
Yun Wang
(University of Ljubljana)
Description
Retrieval-augmented generation (RAG) is becoming an important tool for scientific literature search and evidence synthesis. Here I introduce the core ideas behind RAG through practical examples from the BioASQ and TREC-RAG benchmarks. The presentation covers evidence retrieval, reranking, grounded answer generation, and evaluation, together with common pitfalls and practical lessons learned from developing competitive systems. The presentation is intended for researchers and fellows from different backgrounds who are interested in using RAG tools in scientific research and understanding its current capabilities and limitations.
Author
Yun Wang
(University of Ljubljana)
Co-author
Prof.
Blaž Zupan