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Author

Koichi Nagatsuka

Observed name: Nagatsuka, Koichi
Institution: Hitachi (Japan)
Observed institutions: Soka University, Hitachi (Japan)
ORCID: 0000-0003-0918-5294
Observed ORCID: 0000-0003-0918-5294
OpenAlex ID: A5026440933
Pre-training a BERT with Curriculum Learning by Increasing Block-Size of Input Text
2021 · Koichi Nagatsuka, Clifford Broni-Bediako, et al. · International conference Recent advances in natural language processing · 17
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Length-Based Curriculum Learning for Efficient Pre-training of Language Models
2022 · Koichi Nagatsuka, Clifford Broni-Bediako, et al. · New Generation Computing · 7
Paraphrase Identification for Twitter by Co-Training Based on Words and Characters
2018 · Koichi Nagatsuka, Masayasu Atsumi · Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems (SCIS&ISIS) · 2
Prediction and Analysis of Drug-Glycoprotein Interactions with Mutual Attention Neural Networks
2022 · Eiji Shinkawa, Koichi Nagatsuka, et al. · Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on Advanced Intelligent Systems (SCIS&ISIS) · 1
Synthetic Data Domain Adaptation for ASR via LLM-Based Text and Phonetic Respelling Augmentation
2026 · Natsuo Yamashita, Koichi Nagatsuka, et al. · IEEE International Conference on Acoustics Speech and Signal Processing
Synthetic Data Domain Adaptation for ASR via LLM-based Text and Phonetic Respelling Augmentation
2026 · Yamashita, Natsuo, Nagatsuka, Koichi, et al. · arXiv (Cornell University)
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Is Micro Domain-Adaptive Pre-Training Effective for Real-World Operations? Multi-Step Evaluation Reveals Potential and Bottlenecks
2026 · Association for Computational Linguistics 2026, Koreeda, Yuta, et al. · Underline Science Inc.
Is Micro Domain-Adaptive Pre-Training Effective for Real-World Operations? Multi-Step Evaluation Reveals Potential and Bottlenecks
2026 · Tsunokake, Masaya, Koreeda, Yuta, et al. · arXiv (Cornell University)
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Is Micro Domain-Adaptive Pre-Training Effective for Real-World Operations? Multi-Step Evaluation Reveals Potential and Bottlenecks
2026 · Masaya Tsunokake, Yuta Koreeda, et al. · Conference of the European Chapter of the Association for Computational Linguistics
Construction of Corpus for Text Simplification by Sentential Alignment based on Decomposable Attention Model
2019 · Koichi Nagatsuka · The Japanese Society for Artificial Intelligence
Construction of dataset for summarization based on the Twitter URL Paraphrase Corpus
2018 · Koichi Nagatsuka · The Japanese Society for Artificial Intelligence
Works count: 12
Citation count: 27
H-index: 2
I10-index: 1
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