Published · NIJOTECH
RAG Scholarly Research Chatbot
A retrieval-augmented system that answers scholarly-research queries over academic sources, built to reduce hallucination in academic settings. My undergraduate final-year project and first research manuscript.
What was hard
Academic answers need evidence, not plausible language. The hard part was making retrieval quality visible and measurable.
What I built
Fine-tuned BAAI/bge-large embeddings over the ACL Anthology and used vector retrieval to ground scholarly answers.
What I learned
Retrieval needs its own evaluation. Measuring the retrieval layer made the improvement against baseline LLM answers concrete.
- Retrieval accuracy
- 97%
- Hallucination
- −15%