5 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CL2025
PLaMo 2 Technical Report
Preferred Networks, :, Kaizaburo Chubachi +24
In this report, we introduce PLaMo 2, a series of Japanese-focused large language models featuring a hybrid Samba-based architecture that transitions to full attention via continua…
cs.CL2024
PLaMo-100B: A Ground-Up Language Model Designed for Japanese Proficiency
Preferred Elements, :, Kenshin Abe +18
We introduce PLaMo-100B, a large-scale language model designed for Japanese proficiency. The model was trained from scratch using 2 trillion tokens, with architecture such as QK No…
cs.LG2021★ 5 cited
A Scaling Law for Synthetic-to-Real Transfer: How Much Is Your Pre-training Effective?
Hiroaki Mikami, Kenji Fukumizu, Shogo Murai +5
Synthetic-to-real transfer learning is a framework in which a synthetically generated dataset is used to pre-train a model to improve its performance on real vision tasks. The most…