arXiv (OAI Expanded)
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REALM: Reliable Expertise-Aware Language Model Fine-Tuning from Noisy Annotations
Supervised fine-tuning of large language models relies on human-annotated data, yet annotation pipelines routinely involve multiple crowdworkers of heterogeneous expertise. Standard practice aggregates labels via majority vote or simple averaging, discarding annotator identity and causing the model
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