7 citations · 34 across the 21 of their papers we have counts for
16 papers
Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities
Kazuki Fujii, Taishi Nakamura, Mengsay Loem +7
Cross-lingual continual pre-training of large language models (LLMs) initially trained on English corpus allows us to leverage the vast amount of English language resources and red…
Building a Large Japanese Web Corpus for Large Language Models
Naoaki Okazaki, Kakeru Hattori, Hirai Shota +7
Open Japanese large language models (LLMs) have been trained on the Japanese portions of corpora such as CC-100, mC4, and OSCAR. However, these corpora were not created for the qua…
Computing the k-th Eigenvalue of Symmetric -Matrices
M. Ridwan Apriansyah, Rio Yokota
The numerical solution of eigenvalue problems is essential in various application areas of scientific and engineering domains. In many problem classes, the practical interest is on…
Cache Optimization and Performance Modeling of Batched, Small, and Rectangular Matrix Multiplication on Intel, AMD, and Fujitsu Processors
Sameer Deshmukh, Rio Yokota, George Bosilca
Factorization and multiplication of dense matrices and tensors are critical, yet extremely expensive pieces of the scientific toolbox. Careful use of low rank approximation can dra…
distributed direct factorization of structured dense matrices using runtime systems
Sameer Deshmukh, Qinxiang Ma, Rio Yokota +1
Structured dense matrices result from boundary integral problems in electrostatics and geostatistics, and also Schur complements in sparse preconditioners such as multi-frontal met…
SegRCDB: Semantic Segmentation via Formula-Driven Supervised Learning
Risa Shinoda, Ryo Hayamizu, Kodai Nakashima +3
Pre-training is a strong strategy for enhancing visual models to efficiently train them with a limited number of labeled images. In semantic segmentation, creating annotation masks…