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cs.CL2026
SHAMS: An Audio-Grounded Pronunciation Benchmark for Levantine Arabic
Ben Sapirstein, Roy Mattar, Guy Mor-Lan +3
Levantine Arabic (LA) is spoken by tens of millions of people, creating a pressing need for shared benchmarks to evaluate LA speech-language technologies. Evaluating such technolog…
cs.CL2026
Location Not Found: Exposing Implicit Local and Global Biases in Multilingual LLMs
Guy Mor-Lan, Omer Goldman, Matan Eyal +6
Multilingual large language models (LLMs) have minimized the fluency gap between languages. This advancement, however, exposes models to the risk of biased behavior, as knowledge a…