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University of Aveiro team details BioASQ 14B biomedical QA system

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The BIT.UA team from the University of Aveiro has detailed their participation in the BioASQ 14B challenge, focusing on biomedical question answering. They implemented a modular system that refactored both retrieval and generation components. For document retrieval, they integrated PostgreSQL's pg_textsearch and Qdrant for efficient indexing and GPU-accelerated similarity search, exploring query expansion techniques. Their answer generation phase utilized an LLM-as-a-judge framework and an agent quorum mechanism for consensus-based answers. AI

RANK_REASON The item is an academic paper detailing a system's performance in a specific challenge. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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University of Aveiro team details BioASQ 14B biomedical QA system

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The item is an academic paper detailing a system's performance in a specific challenge. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Andr\'e Ribeiro, R\'uben Garrido, Alexander Christiansen, Richard A. A. Jonker, S\'ergio Matos ·

    BIT.UA at BioASQ 14B: Modular Retrieval with pg_textsearch and Qdrant, and Agent-Based Answer Generation

    arXiv:2609.04999v1 Announce Type: new Abstract: This paper describes the participation of the BIT.UA team from the University of Aveiro in the 14th edition of the BioASQ Task B challenge on biomedical question answering. Building on our previous submissions, we introduced a subst…

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