Papers by Frank Kramer

2 papers
GottBERT: a pure German Language Model (2024.emnlp-main)

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Challenge: Pre-trained language models have advanced natural language processing (NLP) despite the introduction of BERT, single-language models are still relevant.
Approach: They present a German singlelanguage RoBERT model pre-trained exclusively on the German portion of the OSCAR dataset.
Outcome: The GottBERT model outperforms the existing models on Named Entity Recognition and text classification tasks.
Infherno: End-to-end Agent-based FHIR Resource Synthesis from Free-form Clinical Notes (2026.eacl-demo)

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Challenge: HL7 FHIR format is a desirable format for clinical data integration and healthcare services.
Approach: They propose an end-to-end framework that adheres to the HL7 FHIR document schema . it uses LLM agents, code execution, and healthcare terminology database tools .
Outcome: The proposed framework adheres to the HL7 FHIR document schema and competes well with a human baseline in predicting FHIr resources from unstructured text.

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