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Profil bibliographique

Alexandra Kulinkina

Informations fournies par OpenAlex. Research Africa ne déduit ni nationalité, ni poste, ni coordonnées personnelles.

4Publications signalées
0Citations signalées
1Affiliations récentes

Les institutions déclarées

Les domaines associés

Topic ModelingArtificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Les publications récentes

Accès ouvert 2026 preprint OpenAlex

Preferred, Not Safer: Pairwise Preference Is a Poor Proxy for Clinical Safety

Fay Elhassan, David Sasu, Alexandra Kulinkina, Lars Klein et autres

We evaluate whether clinician pairwise preferences provide a reliable signal of clinical safety in large language model (LLM) evaluation using expert feedback from MOOVE (Massive Open Online Validation and Evaluation), a clinician-led platform collecting blinded pairwise preferences alongside multi-criterion rubric ratings. Clinicians …

0 citations arXiv (Cornell University)
Accès ouvert 2026 preprint OpenAlex

Preferred, Not Safer: Pairwise Preference Is a Poor Proxy for Clinical Safety

Fay Elhassan, David Sasu, Alexandra Kulinkina, Lars Klein et autres

We evaluate whether clinician pairwise preferences provide a reliable signal of clinical safety in large language model (LLM) evaluation using expert feedback from MOOVE (Massive Open Online Validation and Evaluation), a clinician-led platform collecting blinded pairwise preferences alongside multi-criterion rubric ratings. Clinicians …

ch (code pays fourni par la source)

0 citations arXiv (Cornell University)
Accès ouvert 2026 preprint OpenAlex

MoBayes: A Modular Bayesian Framework for Separating Reasoning from Language in Conversational Clinical Decision Support

Yusuf Kesmen, Fay Elhassan, Jiayi Ma, Julien Stalhandske et autres

Large language models (LLMs) are increasingly used for conversational clinical decision support, yet they conflate next token prediction with probabilistic decision making. We argue that this conflation reflects an architectural limitation: such systems lack explicit posterior tracking, controllable abstention thresholds, and auditable …

0 citations arXiv (Cornell University)
Accès ouvert 2026 preprint OpenAlex

MoBayes: A Modular Bayesian Framework for Separating Reasoning from Language in Conversational Clinical Decision Support

Yusuf Kesmen, Fay Elhassan, Jiayi Ma, Julien Stalhandske et autres

Large language models (LLMs) are increasingly used for conversational clinical decision support, yet they conflate next token prediction with probabilistic decision making. We argue that this conflation reflects an architectural limitation: such systems lack explicit posterior tracking, controllable abstention thresholds, and auditable …

ch, dk (code pays fourni par la source)

0 citations arXiv (Cornell University)

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