12 citations · 30 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
A Judge-free LLM Open-ended Generation Benchmark Based on the Distributional Hypothesis
Kentaro Imajo, Masanori Hirano, Shuji Suzuki +1
Evaluating the open-ended text generation of large language models (LLMs) is challenging because of the lack of a clear ground truth and the high cost of human or LLM-based assessm…
Enhancing Financial Domain Adaptation of Language Models via Model Augmentation
Kota Tanabe, Masanori Hirano, Kazuki Matoya +3
The domain adaptation of language models, including large language models (LLMs), has become increasingly important as the use of such models continues to expand. This study demons…
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…
The Construction of Instruction-tuned LLMs for Finance without Instruction Data Using Continual Pretraining and Model Merging
Masanori Hirano, Kentaro Imajo
This paper proposes a novel method for constructing instruction-tuned large language models (LLMs) for finance without instruction data. Traditionally, developing such domain-speci…
Construction of Domain-specified Japanese Large Language Model for Finance through Continual Pre-training
Masanori Hirano, Kentaro Imajo
Large language models (LLMs) are now widely used in various fields, including finance. However, Japanese financial-specific LLMs have not been proposed yet. Hence, this study aims…