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cs.CL2025
Towards Trustworthy Lexical Simplification: Exploring Safety and Efficiency with Small LLMs
Akio Hayakawa, Stefan Bott, Horacio Saggion
Despite their strong performance, large language models (LLMs) face challenges in real-world application of lexical simplification (LS), particularly in privacy-sensitive and resou…
cs.CL2025★ 2 cited
UniversalCEFR: Enabling Open Multilingual Research on Language Proficiency Assessment
Joseph Marvin Imperial, Abdullah Barayan, Regina Stodden +16
We introduce UniversalCEFR, a large-scale multilingual and multidimensional dataset of texts annotated with CEFR (Common European Framework of Reference) levels in 13 languages. To…