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e5_large

modelactivee5-large-54383529·2 events·first seen 26d ago

Aliases: e5_large, e5-sk-large

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Recent events (2)

4arXiv · cs.CL·26d ago·source ↗

Automated ICD Classification of Psychiatric Diagnoses Using NLP and LLMs

This study evaluates NLP and ML approaches for automating the mapping of free-text psychiatric descriptions to ICD diagnostic codes, using a dataset of 145,513 Spanish clinical records. Methods range from classical BoW/TF-IDF representations to transformer-based embeddings including e5_large, BioLORD, and Llama-3-8B. Fine-tuned e5_large achieved the best performance with a micro-F1 of 0.866, outperforming classical methods by capturing semantic nuance and medical terminology. The work highlights challenges of long-tail label distributions and ambiguity specific to psychiatric clinical language.

3arXiv · cs.LG·5d ago·source ↗

SkMTEB: First comprehensive MTEB-style text embedding benchmark for Slovak with adapted E5 models

Researchers introduce SkMTEB, the first MTEB-style embedding benchmark for Slovak, covering 31 datasets across 7 task types — roughly 4× the existing multilingual benchmark coverage for the language. Evaluation of 31 embedding models shows large instruction-tuned multilingual models outperform Slovak-specific NLU models on embedding tasks. The authors also release e5-sk-small (45M) and e5-sk-large (365M), derived from Multilingual E5 via vocabulary trimming and fine-tuning, achieving competitive performance with proprietary APIs at up to 62% size reduction.