4 papers
Towards Reliable Retrieval in RAG Systems for Large Legal Datasets
Markus Reuter, Tobias Lingenberg, Rūta Liepiņa +5
Retrieval-Augmented Generation (RAG) is a promising approach to mitigate hallucinations in Large Language Models (LLMs) for legal applications, but its reliability is critically de…
MedSyn: Enhancing Diagnostics with Human-AI Collaboration
Burcu Sayin, Ipek Baris Schlicht, Ngoc Vo Hong +4
Clinical decision-making is inherently complex, often influenced by cognitive biases, incomplete information, and case ambiguity. Large Language Models (LLMs) have shown promise as…
MedGellan: LLM-Generated Medical Guidance to Support Physicians
Debodeep Banerjee, Burcu Sayin, Stefano Teso +1
Medical decision-making is a critical task, where errors can result in serious, potentially life-threatening consequences. While full automation remains challenging, hybrid framewo…
Do LLMs Provide Consistent Answers to Health-Related Questions across Languages?
Ipek Baris Schlicht, Zhixue Zhao, Burcu Sayin +2
Equitable access to reliable health information is vital for public health, but the quality of online health resources varies by language, raising concerns about inconsistencies in…