arXiv · 2604.08549
VerifAI: A Verifiable Open-Source Search Engine for Biomedical Question Answering
Abstract
We introduce VerifAI, an open-source expert system for biomedical question answering that integrates retrieval-augmented generation (RAG) with a novel post-hoc claim verification mechanism. Unlike standard RAG systems, VerifAI ensures factual consistency by decomposing generated answers into atomic claims and validating them against retrieved evidence using a fine-tuned natural language inference (NLI) engine. The system comprises three modular components: (1) a hybrid Information Retrieval (IR) module optimized for biomedical queries (MAP@10 of 42.7%), (2) a citation-aware Generative Component fine-tuned on a custom dataset to produce referenced answers, and (3) a Verification Component that detects hallucinations with state-of-the-art accuracy, outperforming GPT-4 on the HealthVer benchmark. Evaluations demonstrate that VerifAI significantly reduces hallucinated citations compared to zero-shot baselines and provides a transparent, verifiable lineage for every claim. The full pipeline, including code, models, and datasets, is open-sourced to facilitate reliable AI deployment in high-stakes domains.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Miloš Košprdić, Adela Ljajić, Bojana Bašaragin, Darija Medvecki, Lorenzo Cassano, Nikola Milošević. 2026-01-16. VerifAI: A Verifiable Open-Source Search Engine for Biomedical Question Answering. https://arxiv.org/abs/2604.08549
Cite the original work for its findings. Save a collection to share your selection of sources.