ALEE: Any-Language Evaluation of Embeddings via English-Centric Minimal Pairs

By Andrianos Michail, Stylianos Psychias, Michelle Wastl, Simon Clematide, R. Sennrich, Juri Opitz. 2026

Subfields: Natural Language Processing, Representation & Self-Supervised Learning, Evaluation & Benchmarks

Citations in the corpus

• Embedding Models Measure in Peculiar Ways (2026, unknown): “Embedding models can either be evaluated through the ‘macro lens’ via large benchmarking suites like MTEB (Muennighoff et al., 2023), or a ‘micro lens’ via focused tasks like recognizing challenging paraphrases (Li et al., 2025; Michail et al., 2026).”