15 citations · 38 across the 12 of their papers we have counts for
16 papers · 1 filter
Investigating Linear Probe Robustness to Linguistic Register, Medical Specialty, and Corpus Shifts in Medical QA
Nishant Mishra, Ameen Abu-Hanna, Iacer Calixto
Linear classifiers trained on hidden states of a large language model (LLM), linear probes, can flag factual errors from a single forward pass. Geometrically, that implies that tru…
Calibrated? Not for Everyone: How Sexual Orientation and Religious Markers Distort LLM Accuracy and Confidence in Medical QA
Alberto Testoni, Iacer Calixto
Safe clinical deployment of Large Language Models (LLMs) requires not only high accuracy but also robust uncertainty calibration to ensure models defer to clinicians when appropria…
FewMMBench: A Benchmark for Multimodal Few-Shot Learning
Mustafa Dogan, Ilker Kesen, Iacer Calixto +2
As multimodal large language models (MLLMs) advance in handling interleaved image-text data, assessing their few-shot learning capabilities remains an open challenge. In this paper…
Detection of Adverse Drug Events in Dutch clinical free text documents using Transformer Models: benchmark study
Rachel M. Murphy, Nishant Mishra, Nicolette F. de Keizer +5
In this study, we establish a benchmark for adverse drug event (ADE) detection in Dutch clinical free-text documents using several transformer models, clinical scenarios, and fit-f…
DistillNote: Toward a Functional Evaluation Framework of LLM-Generated Clinical Note Summaries
Heloisa Oss Boll, Antonio Oss Boll, Leticia Puttlitz Boll +2
Large language models (LLMs) are increasingly used to generate summaries from clinical notes. However, their ability to preserve essential diagnostic information remains underexplo…
DeVisE: Behavioral Testing of Medical Large Language Models
Camila Zurdo Tagliabue, Heloisa Oss Boll, Aykut Erdem +2
Large language models (LLMs) are increasingly applied in clinical decision support, yet current evaluations rarely reveal whether their outputs reflect genuine medical reasoning or…