
Lead Student Researcher/First Author
FinDVer · Supervised by Prof. Zhen Bi, Huzhou Normal University
June 2026 – Present
Financial claim verification: a multi-agent pipeline that matches cloud-only accuracy at about half the cost
What I did
- Designed and built a multi-agent pipeline for automated financial claim verification on the FinDVer benchmark, matching cloud-only accuracy at ~50% of inference cost across 1,700 held-out claims.
- Architected the routing system and run loop that decide whether each claim goes to a local 3B/7B model or a cloud API call.
- Created two custom verification skills for the pipeline that further cut cloud calls by 20% while continuing to tie cloud-only accuracy.
- Built a BM25 retriever that retrieves 75.2% of gold evidence, 5.4 points above the best published retrieval model on FinDVer.
Tools
Python · Ollama · DeepSeek API · NumPy · LaTeX