Scientific QA System with Verifiable Answers

2024-07-16 · Adela Ljajić, Miloš Košprdić, Bojana Bašaragin, Darija Medvecki, Lorenzo Cassano, Nikola Milošević

In this paper, we introduce the VerifAI project, a pioneering open-source scientific question-answering system, designed to provide answers that are not only referenced but also automatically vetted and verifiable. The components of the system are (1) an Information Retrieval system combining semantic and lexical search techniques over scientific papers (PubMed), (2) a Retrieval-Augmented Generation (RAG) module using fine-tuned generative model (Mistral 7B) and retrieved articles to generate claims with references to the articles from which it was derived, and (3) a Verification engine, based on a fine-tuned DeBERTa and XLM-RoBERTa models on Natural Language Inference task using SciFACT dataset. The verification engine cross-checks the generated claim and the article from which the claim was derived, verifying whether there may have been any hallucinations in generating the claim. By leveraging the Information Retrieval and RAG modules, Verif.ai excels in generating factual information from a vast array of scientific sources. At the same time, the Verification engine rigorously double-checks this output, ensuring its accuracy and reliability. This dual-stage process plays a crucial role in acquiring and confirming factual information, significantly enhancing the information landscape. Our methodology could significantly enhance scientists' productivity, concurrently fostering trust in applying generative language models within scientific domains, where hallucinations and misinformation are unacceptable.

📄 PDF Abstract BibTeX arXiv:2407.11485

Code (1)

nikolamilosevic86/verif.ai pytorch

Tasks

Articles Information Retrieval Misinformation Natural Language Inference Question Answering RAG RetrievalRetrieval-augmented Generation

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Verif.ai: Towards an Open-Source Scientific Generative Question-Answering System with Referenced and Verifiable Answers

2024-02-09 · Miloš Košprdić, Adela Ljajić, Bojana Bašaragin, Darija Medvecki 외

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 informa…

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