2 citations · 2 across the 7 of their papers we have counts for
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Cost-Pragmatic Quality Gating and Selection-Fusion Multi-Model Combiners for BioASQ Phases A+ and B
Dima Galat, Marian-Andrei Rizoiu
We describe our BioASQ Task 14B 2026 system. The work centers on two design decisions: how aggressively to re-retrieve when first-stage retrieval is weak, and how to combine multip…
LLM Ensemble for RAG: Role of Context Length in Zero-Shot Question Answering for BioASQ Challenge
Dima Galat, Diego Molla-Aliod
Biomedical question answering (QA) poses significant challenges due to the need for precise interpretation of specialized knowledge drawn from a vast, complex, and rapidly evolving…
Advancing LLM detection in the ALTA 2024 Shared Task: Techniques and Analysis
Dima Galat
The recent proliferation of AI-generated content has prompted significant interest in developing reliable detection methods. This study explores techniques for identifying AI-gener…
Enhancing Biomedical Text Summarization and Question-Answering: On the Utility of Domain-Specific Pre-Training
Dima Galat, Marian-Andrei Rizoiu
Biomedical summarization requires large datasets to train for text generation. We show that while transfer learning offers a viable option for addressing this challenge, an in-doma…
Query-Focused Extractive Summarisation for Finding Ideal Answers to Biomedical and COVID-19 Questions
Diego Mollá, Urvashi Khanna, Dima Galat +2
This paper presents Macquarie University's participation to the BioASQ Synergy Task, and BioASQ9b Phase B. In each of these tasks, our participation focused on the use of query-foc…