collaborators

12 papers

cs.DB2026

Beyond Scale and Generation: Understanding Language Model-based Entity Matching

Zeyu Zhang, Xue Li, Iacer Calixto +2

Entity matching identifies records that refer to the same real-world entity. Language models can be adapted to this task through bi-encoder, cross-encoder, and generative matcher a…

cs.CL2026

MedPath: Multi-Domain Cross-Vocabulary Hierarchical Paths for Biomedical Entity Linking

Nishant Mishra, Wilker Aziz, Iacer Calixto

Progress in biomedical Named Entity Recognition (NER) and Entity Linking (EL) is currently hindered by a fragmented data landscape, a lack of resources for building explainable mod…

cs.CL2026

Uncertainty Is Not a Safety Net for Clinical VQA, but Can It Anticipate Model Failure?

Arnisa Fazla, Alberto Testoni, Ameen Abu-Hanna +2

Safe deployment of clinical vision-language models (VLMs) requires reliable uncertainty estimation (UE): a signal indicating when predictions should be trusted or escalated to a cl…

cs.CR2026

Differentially Private De-identification of Dutch Clinical Notes: A Comparative Evaluation

Michele Miranda, Xinlan Yan, Nishant Mishra +4

Protecting patient privacy in clinical narratives is essential for enabling secondary use of healthcare data under regulations such as GDPR and HIPAA. While manual de-identificatio…

cs.CL2026

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…

cs.CL2026

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…