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Masaaki Nagata

Observed names: Nagata Masaaki, Nagata, Masaaki, 永田 昌明
OpenAlex ID: A5131825541
Reducing Odd Generation from Neural Headline Generation
2018 · Kiyono, Shun, 94160, et al. · Institutional Repositories DataBase (IRDB) · 3
The Current State of Machine Translation in the LLM Era: From Next-word Prediction to Reasoning
2026 · Masaaki Nagata · NTT technical review
NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning
2026 · Association for Computational Linguistics 2026, Miao, Zhongtao, et al. · Underline Science Inc.
Argument Mining as a Text-to-Text Generation Task
2026 · Kawarada, Masayuki, Hirao, Tsutomu, et al. · arXiv (Cornell University)
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NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning
2026 · Miao, Zhongtao, Zhao, Kaiyan, et al. · arXiv (Cornell University)
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LlmMT+1: Enhancing Non-dominant Language Pair in Large Language Model-based Machine Translation
2026 · Xinger Fu, Masaaki Nagata, et al. · Journal of Natural Language Processing
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Automatic Post-editing through Word-level Quality Estimation with Minimum Bayes Risk Decoding
2026 · Youyuan Lin, Masaaki Nagata, et al. · Journal of Natural Language Processing
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NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning
2026 · Zhongtao Miao, Kaiyan Zhao, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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Findings of the WMT26 General Machine Translation Shared Task: Contrastive Dynamic Human Evaluation at Scale
2026 · Tom Kocmi, Ekaterina Artemova, et al. · Conference on Machine Translation (WMT)
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Two Step Automatic Post Editing of Patent Machine Translation based on Pre-trained Encoder Models and LLMs
2025 · Kosei Buma, Takehito Utsuro, et al. · International Joint Conference on Natural Language Processing and Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL)
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A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
2022 · 小林, 尚輝, Kobayashi, Naoki, et al. · Institutional Repositories DataBase (IRDB)
Effectiveness of Syntactic Dependency Information for Higher-Order Syntactic Attention Network
2021 · 上垣外 英剛, Hidetaka Kamigaito, et al. · Institutional Repositories DataBase (IRDB)
Improving Neural RST Parsing Model with Silver Agreement Subtrees
2021 · 小林, 尚輝, Kobayashi, Naoki, et al. · Institutional Repositories DataBase (IRDB)
Top-down RST Parsing Utilizing Granularity Levels in Documents
2020 · 小林, 尚輝, Kobayashi, Naoki, et al. · Institutional Repositories DataBase (IRDB)
Context-aware Neural Machine Translation with Coreference Information
2019 · 大谷, 拓海, Ohtani, Takumi, et al. · Institutional Repositories DataBase (IRDB)
Split or Merge: Which is Better for Unsupervised RST Parsing?
2019 · 小林, 尚輝, Kobayashi, Naoki, et al. · Institutional Repositories DataBase (IRDB)
Works count: 22
Citation count: 3
H-index: 1
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