4 citations · 9 across the 10 of their papers we have counts for
5 papers · 1 filter
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…
Zoom In Disparities in Healthcare LLM Q&A
Ipek Baris Schlicht, Burcu Sayin, Zhixue Zhao +5
Equitable access to reliable health information is vital when integrating AI into healthcare. Yet, information quality varies across languages, raising concerns about the reliabili…
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…