2 citations · 2 across the 3 of their papers we have counts for
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cs.CL2026
Is Micro Domain-Adaptive Pre-Training Effective for Real-World Operations? Multi-Step Evaluation Reveals Potential and Bottlenecks
Masaya Tsunokake, Yuta Koreeda, Terufumi Morishita +3
When applying LLMs to real-world enterprise operations, LLMs need to handle proprietary knowledge in small domains of specific operations (). A previous stu…
cs.CL2025
Agent Fine-tuning through Distillation for Domain-specific LLMs in Microdomains
Yawen Xue, Masaya Tsunokake, Yuta Koreeda +3
Agentic large language models (LLMs) have become prominent for autonomously interacting with external environments and performing multi-step reasoning tasks. Most approaches levera…
cs.CL2023★ 2 cited
Hitachi at SemEval-2023 Task 3: Exploring Cross-lingual Multi-task Strategies for Genre and Framing Detection in Online News
Yuta Koreeda, Ken-ichi Yokote, Hiroaki Ozaki +3
This paper explains the participation of team Hitachi to SemEval-2023 Task 3 "Detecting the genre, the framing, and the persuasion techniques in online news in a multi-lingual setu…