Kazuma Hashimoto

Kazuma is a researcher working in the area of Natural Language Processing (NLP). After experiencing research on various NLP topics (word/phrase representation learning, multi-task learning, machine translation, goal oriented-dialogue, question answering, etc.), here at Google Research he is focusing on search-related NLP topics.

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    Google
Take One Step at a Time to Know Incremental Utility of Demonstration: An Analysis on Reranking for Few-Shot In-Context Learning
Kazuma Hashimoto
Karthik Raman
Michael Bendersky
NAACL (2024)
How Does Beam Search improve Span-Level Confidence Estimation in Generative Sequential Labeling?
Kazuma Hashimoto
Iftekhar Naim
Karthik Raman
EACL 2024 workshop on UncertaiNLP
Exploring the Viability of Synthetic Query Generation for Relevance Prediction
Aditi Chaudhary
Karthik Raman
Krishna Srinivasan
Kazuma Hashimoto
Michael Bendersky
Marc Najork
SIGIR (2023)
Transforming Sequence Tagging Into A Seq2Seq Task
Karthik Raman
Iftekhar Naim
Jiecao Chen
Kazuma Hashimoto
Kiran Yalasangi
Krishna Srinivasan
EMNLP 2022
GROOT: Corrective Reward Optimization for Generative Sequential Labeling
Kazuma Hashimoto
Karthik Raman
arXiv (2022)
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