activity
20232026
most citedFrom Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot Contexts

19 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR2026

VerifAI: A Verifiable Open-Source Search Engine for Biomedical Question Answering

Miloš Košprdić, Adela Ljajić, Bojana Bašaragin +3

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 m…

cs.CL2024

Scientific QA System with Verifiable Answers

Adela Ljajić, Miloš Košprdić, Bojana Bašaragin +3

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 au…

cs.CL2024

How do you know that? Teaching Generative Language Models to Reference Answers to Biomedical Questions

Bojana Bašaragin, Adela Ljajić, Darija Medvecki +3

Large language models (LLMs) have recently become the leading source of answers for users' questions online. Despite their ability to offer eloquent answers, their accuracy and rel…

cs.IR2024★ 1 cited

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

Miloš Košprdić, Adela Ljajić, Bojana Bašaragin +2

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 com…

cs.CL2023★ 19 cited

From Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot Contexts

Miloš Košprdić, Nikola Prodanović, Adela Ljajić +2

Supervised named entity recognition (NER) in the biomedical domain depends on large sets of annotated texts with the given named entities. The creation of such datasets can be time…