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cs.CL2026
emb-diversity: A Tool for Embedding-Based Measurement of Data Diversity
Cantao Su, Menan Velayuthan, Esther Ploeger +2
There is growing evidence that data diversity is crucial for developing fair and robust NLP models. However, current approaches to measure diversity remain inconsistent and fragmen…
cs.CL2026
STEB: Style Text Embedding Benchmark
Rafael Rivera Soto, Anna Wegmann, Cristina Aggazzotti
While semantic embeddings are rigorously evaluated on the Massive Text Embedding Benchmark, the evaluation of style embeddings remains fragmented, with each work relying on their o…