Presents the first fully open pipeline for clinical LLMs that unifies eight public QA datasets with clinician-vetted synthetic data from guidelines and vignettes, achieving improved performance on medical benchmarks while enabling full auditability.
Winogrande: An adversarial Winograd schema challenge at scale.Communications of the ACM, 64(9):99–106, 2021
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Parcae stabilizes looped LLMs via spectral norm constraints on injection parameters, enabling power-law scaling for training FLOPs and saturating exponential scaling at test time that improves quality over fixed-depth baselines under fixed parameter budgets.
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Fully Open Meditron: An Auditable Pipeline for Clinical LLMs
Presents the first fully open pipeline for clinical LLMs that unifies eight public QA datasets with clinician-vetted synthetic data from guidelines and vignettes, achieving improved performance on medical benchmarks while enabling full auditability.
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Parcae: Scaling Laws For Stable Looped Language Models
Parcae stabilizes looped LLMs via spectral norm constraints on injection parameters, enabling power-law scaling for training FLOPs and saturating exponential scaling at test time that improves quality over fixed-depth baselines under fixed parameter budgets.