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A collection of 650+ Apache-2.0 licensed biomedical NER and de-identification models that run on-device via MLX, achieving 30-40x faster inference than PyTorch-CPU on an M3 Max with identical outputs.
This paper proposes an iterative moderation framework that refines and reuses annotation guidelines to improve LLM-based annotation performance, validated on biomedical NER tasks with GPT, Gemini, and DeepSeek models.
This paper presents a corpus-centric diagnostic framework for analyzing biomedical NER and EL benchmarks, revealing substantial differences across nine corpora and arguing that standard statistics are insufficient for characterizing evaluation demands.