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cs.CL2026
Extending Item Response Theory for Efficient and Meaningful Multilingual Evaluation
Gili Lior, Tzviel Frostig, Gabriel Stanovsky +1
Multilingual benchmarks are central to evaluating large language models (LLMs) across languages, but they suffer from three issues: exhaustive evaluation scales linearly with the n…
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…