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Found 4 papers, 2 papers with code
MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
Large language models (LLMs) can potentially democratize access to medical knowledge.
Ranked #1 on
Multiple Choice Question Answering (MCQA)
on MedMCQA
(Dev Set (Acc-%) metric)
Conditional Text Generation
Multiple Choice Question Answering (MCQA)
DoGE: Domain Reweighting with Generalization Estimation
Moreover, aiming to generalize to out-of-domain target tasks, which is unseen in the pretraining corpus (OOD domain), DoGE can effectively identify inter-domain dependencies, and consistently achieves better test perplexity on the target domain.
Irreducible Curriculum for Language Model Pretraining
Automatic data selection and curriculum design for training large language models is challenging, with only a few existing methods showing improvements over standard training.
Towards Process-Oriented, Modular, and Versatile Question Generation that Meets Educational Needs
NLP-powered automatic question generation (QG) techniques carry great pedagogical potential of saving educators' time and benefiting student learning.
