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This paper describes UOL@IDEM's closed-track submission to the BEA 2026 shared task on L1-aware vocabulary difficulty prediction, combining multilingual contextual representations with engineered features. The system achieves competitive RMSE scores for Spanish, German, and Chinese, with frequency being the most stable predictor.