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Mai Mohamed Eida

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#natural language process... Preprint Sep 2026

From Tables to Quantified Statements: Evaluating LLM Inference Generation through Executable Verification

This work introduces STAT-TO-TEXT, a controlled task in which LLMs generate quantified natural language inferences from statistical tables using quantified constructions such as all, some, no, and most, and uses an LLM generated Python checker code to evaluate these inferences.

Mai Mohamed Eida, Gunjan Anand, Ashutosh Kumar Singh et al. · 0 citations

#natural language process... Preprint Sep 2026

Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs

Previous work on Egyptian Arabic in NLP has focused largely on the prestigious Cairene Egyptian Arabic (CEA) dialect, resulting in a lack of representation for the less prestigious Sa'idi Egyptian Arabic (SEA) dialect both in LLM and resource development. Does this lack of representation influence an LLM's view of the...

Mai Mohamed Eida, Ryan Dolan, Paul Leonce Irma De Nijs et al. · 0 citations