2 citations · 2 across the 4 of their papers we have counts for
10 papers
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…
Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Care
Burcu Sayin, Ngoc Vo Hong, Ipek Baris Schlicht +8
Clinical decision-making in emergency medicine demands rapid, accurate diagnoses under uncertainty. Despite benchmark progress, evidence for LLMs as interactive aids in live physic…
Hybrid Decision Making via Conformal VLM-generated Guidance
Debodeep Banerjee, Burcu Sayin, Stefano Teso +1
Building on recent advances in AI, hybrid decision making (HDM) holds the promise of improving human decision quality and reducing cognitive load. We work in the context of learnin…
Learning To Guide Human Decision Makers With Vision-Language Models
Debodeep Banerjee, Stefano Teso, Burcu Sayin +1
There is growing interest in AI systems that support human decision-making in high-stakes domains (e.g., medical diagnosis) to improve decision quality and reduce cognitive load. M…
Towards Reliable Retrieval in RAG Systems for Large Legal Datasets
Markus Reuter, Tobias Lingenberg, RÅ«ta LiepiÅa +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…
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…