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cs.CL2026
Training a Large Language Model for Medical Coding Using Privacy-Preserving Synthetic Clinical Data
John Cook, Michael Wyatt, Peng Wei +11
Improving the accuracy and reliability of medical coding reduces clinician burnout and supports revenue cycle processes, freeing providers to focus more on patient care. However, a…
cs.CL2024
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Marah Abdin, Jyoti Aneja, Hany Awadalla +126
We introduce phi-3-mini, a 3.8 billion parameter language model trained on 3.3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal test…