Nakamura, Taishi

9 publications

TMLR 2026 MixtureVitae: Open Web-Scale Pretraining Dataset with High Quality Instruction and Reasoning Data Built from Permissive-First Text Sources Huu Nguyen, Victor May, Harsh Raj, Marianna Nezhurina, Yishan Wang, Yanqi Luo, Vu Minh Chien, Taishi Nakamura, Ken Tsui, Van Khue Nguyen, David Salinas, Aleksandra Krasnodębska, Christoph Schuhmann, Mats Leon Richter, Xuan-Son Vu, Jenia Jitsev

ICLR 2026 Optimal Sparsity of Mixture-of-Experts Language Models for Reasoning Tasks Taishi Nakamura, Satoki Ishikawa, Masaki Kawamura, Takumi Okamoto, Daisuke Nohara, Jun Suzuki, Rio Yokota

ICLR 2026 Rewriting Pre-Training Data Boosts LLM Performance in Math and Code Kazuki Fujii, Yukito Tajima, Sakae Mizuki, Masaki Kawamura, Hinari Shimada, Taihei Shiotani, Koshiro Saito, Masanari Oi, Taishi Nakamura, Takumi Okamoto, Shigeki Ishida, Kakeru Hattori, Youmi Ma, Hiroya Takamura, Rio Yokota, Jun Sakuma, Naoaki Okazaki

ICLR 2025 Agent Skill Acquisition for Large Language Models via CycleQD So Kuroki, Taishi Nakamura, Takuya Akiba, Yujin Tang

ICLR 2025 Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-Initialization Taishi Nakamura, Takuya Akiba, Kazuki Fujii, Yusuke Oda, Rio Yokota, Jun Suzuki

NeurIPS 2025 Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search Yuichi Inoue, Kou Misaki, Yuki Imajuku, So Kuroki, Taishi Nakamura, Takuya Akiba

ICLRW 2025 Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search Kou Misaki, Yuichi Inoue, Yuki Imajuku, So Kuroki, Taishi Nakamura, Takuya Akiba

NeurIPSW 2024 Agent Skill Acquisition for LLMs via CycleQD So Kuroki, Taishi Nakamura, Takuya Akiba, Yujin Tang

NeurIPSW 2024 Agent Skill Acquisition for Large Language Models via CycleQD So Kuroki, Taishi Nakamura, Takuya Akiba, Yujin Tang