Verif.ai: Towards an Open-Source Scientific Generative
  Question-Answering System with Referenced and Verifiable Answers
Miloš Košprdić Adela Ljajić Bojana Bašaragin Darija Medvecki Nikola Milošević
In this paper, we present the current progress of the project Verif.ai, an
open-source scientific generative question-answering system with referenced and
verified answers. The components of the system are (1) an information retrieval
system combining semantic and lexical search techniques over scientific papers
(PubMed), (2) a fine-tuned generative model (Mistral 7B) taking top answers and
generating answers with references to the papers from which the claim was
derived, and (3) a verification engine that cross-checks the generated claim
and the abstract or paper from which the claim was derived, verifying whether
there may have been any hallucinations in generating the claim. We are
reinforcing the generative model by providing the abstract in context, but in
addition, an independent set of methods and models are verifying the answer and
checking for hallucinations. Therefore, we believe that by using our method, we
can make scientists more productive, while building trust in the use of
generative language models in scientific environments, where hallucinations and
misinformation cannot be tolerated.