---
title: "Who cites Kakeru Hattori — 119 papers of our library"
description: "119 papers of the Elamur Research library cite the works of Kakeru Hattori, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/kakeru-hattori/cited-by/"
---
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# Who cites Kakeru Hattori

122 citations of their works from 119 papers of our library (of the 149,439 whose bibliographies we read) · 32 with a page here, the most cited first · [← Kakeru Hattori](https://md.research.elamur.ai/free/en/authors/kakeru-hattori/)

1. [**Kimi K2: Open Agentic Intelligence arXiv:2507.20534**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 347 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
2. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
3. **[SemEval-2026 Task 13: Detecting Machine-Generated Code with Multiple Programming Languages, Generators, and Application Scenarios](https://md.research.elamur.ai/free/en/papers/orel-2026-semeval-2026-task-13-detecting/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 41 citations*
4. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
5. [**Beyond English-Centric LLMs: What Language Do Multilingual Language Models Think in? arXiv:2408.10811**Chengzhi Zhong, Fei Cheng, Qianying Liu, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-english-centric-llms-language-multilingual/)
6. **[AICD Bench: A Challenging Benchmark for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/orel-2026-aicd-bench-challenging-benchmark-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 23 citations*
7. **[Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation](https://md.research.elamur.ai/free/en/papers/iyer-2024-quality-quantity-data-scale-diversity/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Vivek Iyer; Bhavitvya Malik; Pavel Stepachev; Pinzhen Chen; Barry Haddow;, Alexandra Birch*2024 · 17 citations*
8. [**Rewriting Pre-Training Data Boosts LLM Performance in Math and Code arXiv:2505.02881**Kazuki Fujii, Yukito Tajima, Sakae Mizuki, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2025-rewriting-pre-training-data-boosts/)
9. **[Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization](https://md.research.elamur.ai/free/en/papers/foroutan-2026-parity-aware-byte-pair-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Negar Foroutan, Clara Meister, Debjit Paul, et al.*2026 · 12 citations*
10. **[How Can We Effectively Expand the Vocabulary of LLMs with 0.01GB of Target Language Text?](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-how-can-we-effectively-expand/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Atsuki Yamaguchi, Aline Villavicencio, Nikolaos Aletras*2026 · 11 citations*
11. [**Bilingual Adaptation of Monolingual Foundation Models arXiv:2407.12869**Gurpreet Gosal, Yishi Xu, Gokul Ramakrishnan, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/gosal-2024-bilingual-adaptation-monolingual-foundation-models/)
12. **[Teaching Old Tokenizers New Words: Efficient Tokenizer Adaptation for Pretrained Models](https://md.research.elamur.ai/free/en/papers/purason-2026-teaching-old-tokenizers-new-words/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taido Purason, Pavel Chizhov, Ivan P. Yamshchikov, et al.*2026 · 4 citations*
13. **[Mitigating Catastrophic Forgetting in Target Language Adaptation of LLMs via Source-Shielded Updates](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-mitigating-catastrophic-forgetting-target-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Atsuki Yamaguchi, Terufumi Morishita, Aline Villavicencio, et al.*2026 · 3 citations*
14. [**A Sovereign, Open-Source Foundation Model for German and English arXiv:2607.09424**Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/droste-2026-sovereign-open-source-foundation-model/)
15. **[Disentangling Continued Pre-Training: Attention-Driven Routing and Semantic Hub Preservation in Language Adaptation](https://md.research.elamur.ai/free/en/papers/tran-2026-disentangling-continued-pre-training-attention/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Khanh-Tung Tran, Vinh-Khanh Tran, Barry O'Sullivan, et al.*2026 · 1 citation*
16. **[“We Are (Language) Family”: Adapting Transformer models to related minority languages with linguistic data](https://md.research.elamur.ai/free/en/papers/otal-2026-we-are-language-family-adapting/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Miguel López-Otal, Jorge Gracia*2026 · 1 citation*
17. **[AraS2P: Arabic Speech-to-Phonemes System](https://md.research.elamur.ai/free/en/papers/mattar-2025-aras2p-arabic-speech-phonemes-system/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Bassam Mattar, Mohamed Fayed, Ayman Khalafallah*2025 · 1 citation*
18. **[A Dialogue System for Second Language Learning with Dynamic Adaptation to In-Dialogue Difficulty Changes](https://md.research.elamur.ai/free/en/papers/morioka-2026-dialogue-system-second-language-learning/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Taku Morioka, Junya Takayama, Tomoyuki Kajiwara*2026*
19. **[Conceptual Cultural Index: A Metric for Cultural Specificity via Relative Generality](https://md.research.elamur.ai/free/en/papers/ohashi-2026-conceptual-cultural-index-metric-cultural/) [Workshop on Multilingual Multicultural Evaluation](https://md.research.elamur.ai/free/en/venues/mme/)**Takumi Ohashi, Hitoshi Iyatomi*2026*
20. **[Diagnosing LLMs via Information Spectrum Analysis: Tail Behavior and the Effects of Side Information](https://md.research.elamur.ai/free/en/papers/tachioka-2026-diagnosing-llms-information-spectrum-analysis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuuki Tachioka*2026*
21. **[Efficient Low-Resource Language Adaptation via Multi-Source Dynamic Logit Fusion](https://md.research.elamur.ai/free/en/papers/zhang-2026-efficient-low-resource-language-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chen Zhang, Jiuheng Lin, Zhiyuan Liao, et al.*2026*
22. **[Emotion Transcription in Conversation: A Benchmark for Capturing Subtle and Complex Emotional States through Natural Language](https://md.research.elamur.ai/free/en/papers/tanaka-2026-emotion-transcription-conversation-benchmark-capturing/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yoshiki Tanaka, Ryuichi Uehara, Koji Inoue, et al.*2026*
23. **[Evaluating the Effect of Question Wording Variations on Answer Consistency in Large Language Models](https://md.research.elamur.ai/free/en/papers/takayama-2026-evaluating-effect-question-wording-variations/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Junya Takayama, Masaya Ohagi, Tomoya Mizumoto, et al.*2026*
24. [**HEBATRON: A Hebrew-Specialized Open-Weight Mixture-of-Experts Language Model**Noam Kayzer, Dan Revital, Ori Bar Joseph, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kayzer-2026-hebatron-hebrew-specialized-open-weight/)
25. **[HOTATE: A Japanese Dialogue Corpus Annotated with Responses of Private Thoughts and Public Statements](https://md.research.elamur.ai/free/en/papers/toda-2026-hotate-japanese-dialogue-corpus-annotated/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuko Toda, Daisuke Maekawa, Kota Manabe, et al.*2026*
26. **[J-ClinicalBench: A Benchmark for Evaluating Large Language Models on Practical Clinical Tasks in Japanese](https://md.research.elamur.ai/free/en/papers/shimizu-2026-j-clinicalbench-benchmark-evaluating-large/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Seiji Shimizu, Tomohiro Nishiyama, HISADA Shohei, et al.*2026*
27. **[JFC-Recipe: A Dataset for Nutrient Estimation from Japanese User-Generated Cooking Recipes](https://md.research.elamur.ai/free/en/papers/shirai-2026-jfc-recipe-dataset-nutrient-estimation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Keisuke Shirai, Yoko Yamakata, Hirotaka Kameko, et al.*2026*
28. **[JSTS-Neg: Japanese Semantic Textual Similarity Dataset for Evaluating Negation Understanding Ability](https://md.research.elamur.ai/free/en/papers/yuasa-2026-jsts-neg-japanese-semantic-textual/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Reiko Yuasa, Yoshihide Kato, Shigeki Matsubara*2026*
29. **[LGSE: Lexically Grounded Subword Embedding Initialization for Low-Resource Language Adaptation](https://md.research.elamur.ai/free/en/papers/teklehaymanot-2026-lgse-lexically-grounded-subword-embedding/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hailay Kidu Teklehaymanot, Dren Fazlija, Wolfgang Nejdl*2026*
30. **[Merging Continual Pretraining Models for Domain-Specialized LLMs: A Case Study in Finance](https://md.research.elamur.ai/free/en/papers/ueda-2026-merging-continual-pretraining-models-domain/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kentaro Ueda, François Portet, Hirohiko Suwa, et al.*2026*
31. **[Parallel Corpus Filtering Based on Semantic Similarity and Surface Dissimilarity for Japanese Text Simplification with LLMs](https://md.research.elamur.ai/free/en/papers/maekawa-2026-parallel-corpus-filtering-based-semantic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Daisuke Maekawa, Tomoyuki Kajiwara, Takashi Ninomiya*2026*
32. [**Reading the News: Adapting Large Language Models to Swedish Journalism Through Continued Pre-Training arXiv:2608.30609**Lukas Borggren, Jenny Kunz, Marco Kuhlmann*2026*](https://md.research.elamur.ai/free/en/papers/borggren-2026-reading-news-adapting-large-language/)

87 more citing papers of our library have no page here yet.

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