Author

Raad Bin Tareaf

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#natural language process... Review Sep 2026

Target leakage, not model class, explains reported accuracy in survey-based cardiovascular screening: a leakage-tiered audit of glass-box and tabular foundation models

This work benchmarked ten classifiers spanning linear, tree-ensemble, neural, glass-box, and tabular foundation classes for prevalent myocardial infarction in 442,067 respondents of the 2022 Behavioral Risk Factor Surveillance System across five feature tiers of decreasing leakage risk.

Raad Bin Tareaf, Murad Al-Rajab, Samia Loucif et al. · 0 citations

#natural language process... Preprint Sep 2026

The widening evaluation gap in medical large language model research 2023 to 2026

Whether medical research is keeping pace with the systems it evaluates is asked, and Rigour and currency are in tension, and that tension reflects model selection rather than research timelines.

Raad Bin Tareaf, Murad Al-Rajab, Samia Loucif · 0 citations

#natural language process... Preprint Aug 2026

Benchmarking large language model agent societies against human behavioural distributions

SILICA is an open instrument that tests three doubts of large language model agents: whether the agents behave like the humans they stand in for, whether a finding survives changes to the apparatus that leave the rules untouched, and whether apparent social dynamics are interaction at all rather than the reproduction o...

Raad Bin Tareaf · 0 citations