Papers by Natália Kňažeková
SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation (2026.acl-long)
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| Challenge: | Slovak embeddings are core infrastructure for semantic search, retrieval-augmented generation (RAG), clustering, and classification. |
| Approach: | They propose a MTEB-style text embedding benchmark for Slovak, a low-resource West Slavic language . they use 31 datasets across 7 task types to evaluate the performance of the models . |
| Outcome: | The proposed model achieves competitive performance with proprietary APIs while remaining locally deployable for RAG . the model is based on 31 datasets across 7 task types and is 4 the depth of existing benchmark for Slovak . |