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title: "Greater Tokyo — works, page 2 — Elamur Research"
description: "Works of Greater Tokyo: 133 in our library · page 2 of 2, the most cited first. Among them: Universal Dependencies for Amharic."
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# Works of Greater Tokyo

133 · page 2 of 2 · the most cited first · [← Greater Tokyo](https://md.research.elamur.ai/free/en/agglomerations/greater-tokyo/)

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101. [**Universal Dependencies for Amharic**Binyam Ephrem Seyoum, Yusuke Miyao, Baye Yimam Mekonnen*2018 · 19 citations*](https://md.research.elamur.ai/free/en/papers/seyoum-2018-universal-dependencies-amharic/)
102. **[Neural Japanese Zero Anaphora Resolution using Smoothed Large-scale Case Frames with Word Embedding](https://md.research.elamur.ai/free/en/papers/yamashiro-neural-japanese-zero-anaphora-resolution/) [Pacific Asia Conference on Language, Information and Computation (PACLIC)](https://md.research.elamur.ai/free/en/venues/paclic/)**Souta Yamashiro, Hitoshi Nishikawa, Takenobu Tokunaga*17 citations*
103. **[A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing](https://md.research.elamur.ai/free/en/papers/kobayashi-2022-simple-strong-baseline-end-end/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Naoki Kobayashi, Tsutomu Hirao, Hidetaka Kamigaito, et al.*2022 · 16 citations*
104. **[Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/konno-2021-pseudo-zero-pronoun-resolution-improves/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryuto Konno, Shun Kiyono, Yuichiroh Matsubayashi, et al.*2021 · 14 citations*
105. **[An Annotated Corpus of Reference Resolution for Interpreting Common Grounding](https://md.research.elamur.ai/free/en/papers/udagawa-2019-annotated-corpus-reference-resolution-interpreting/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Takuma Udagawa, Akiko Aizawa*2019 · 14 citations*
106. **[SSA-COMET: Do LLMs Outperform Learned Metrics in Evaluating MT for Under-Resourced African Languages?](https://md.research.elamur.ai/free/en/papers/li-2025-ssa-comet-do-llms-outperform/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Senyu Li, Jiayi Wang, Felermino D. M. A. Ali, et al.*2025 · 13 citations*
107. **[Maintaining Common Ground in Dynamic Environments](https://md.research.elamur.ai/free/en/papers/udagawa-2021-maintaining-common-ground-dynamic-environments/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Takuma Udagawa, Akiko Aizawa*2021 · 13 citations*
108. [**Effective Use of Function Words for Rule Generalization in Forest-Based Translation**Xianchao Wu, Takuya Matsuzaki, Jun'ichi Tsujii*2011 · 13 citations*](https://md.research.elamur.ai/free/en/papers/wu-2011-effective-use-function-words-rule/)
109. [**Descriptive and Empirical Approaches to Capturing Underlying Dependencies among Parsing Errors**Tadayoshi Hara, Yusuke Miyao, Jun'ichi Tsujii*2009 · 11 citations*](https://md.research.elamur.ai/free/en/papers/hara-2009-descriptive-empirical-approaches-capturing-underlying/)
110. [**A POS Tagging Model Designed for Learner English**Ryo Nagata, Tomoya Mizumoto, Yuta Kikuchi, et al.*2018 · 11 citations*](https://md.research.elamur.ai/free/en/papers/nagata-2018-pos-tagging-model-adapted-learner/)
111. **[An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/konno-2020-empirical-study-contextual-data-augmentation/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Ryuto Konno, Yuichiroh Matsubayashi, Shun Kiyono, et al.*2020 · 9 citations*
112. **[BabyLM Challenge: Curriculum learning based on sentence complexity approximating language acquisition](https://md.research.elamur.ai/free/en/papers/oba-2023-babylm-challenge-curriculum-learning-based/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Miyu Oba, Akari Haga, Akiyo Fukatsu, et al.*2023 · 9 citations*
113. **[Analysis of English Spelling Errors in a Word-Typing Game](https://md.research.elamur.ai/free/en/papers/tachibana-2016-analysis-english-spelling-errors-word/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ryuichi Tachibana, Mamoru Komachi*2016 · 9 citations*
114. **[An Evaluation Dataset for Identifying Communicative Functions of Sentences in English Scholarly Papers](https://md.research.elamur.ai/free/en/papers/iwatsuki-2020-evaluation-dataset-identifying-communicative-functions/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kenichi Iwatsuki, Florian Boudin, Akiko Aizawa*2020 · 8 citations*
115. [**Exploring Difficulties in Parsing Imperatives and Questions**Tadayoshi Hara, Takuya Matsuzaki, Yusuke Miyao, et al.*2011 · 6 citations*](https://md.research.elamur.ai/free/en/papers/hara-2011-exploring-difficulties-parsing-imperatives-questions/)
116. **[A Large-Scale Corpus of E-mail Conversations with Standard and Two-Level Dialogue Act Annotations](https://md.research.elamur.ai/free/en/papers/taniguchi-2020-large-scale-corpus-e-mail/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Motoki Taniguchi, Yoshihiro Ueda, Tomoki Taniguchi, et al.*2020 · 6 citations*
117. **[Decoding, Fast and Slow: A Case Study on Balancing Trade-Offs in Incremental, Character-level Pragmatic Reasoning](https://md.research.elamur.ai/free/en/papers/zarriess-2021-decoding-fast-slow-case-study/) [International Natural Language Generation Conference (INLG)](https://md.research.elamur.ai/free/en/venues/inlg/)**Sina Zarrieß, Hendrik Buschmeier, Ting Han, et al.*2021 · 6 citations*
118. **[Sub-lexical Dialogue Act Classification in a Spoken Dialogue System Support for the Elderly with Cognitive Disabilities](https://md.research.elamur.ai/free/en/papers/sadohara-2013-sub-lexical-dialogue-act-classification/) [Workshop on Speech and Language Processing for Assistive Technologies](https://md.research.elamur.ai/free/en/venues/workshop-on-speech-and-language-processing-for-assistive-technologies/)**Ken Sadohara, Hiroaki Kojima, Takuya Narita, et al.*2013 · 5 citations*
119. [**Effective Analysis of Causes and Inter-dependencies of Parsing Errors**Tadayoshi Hara, Yusuke Miyao, Jun'ichi Tsujii*2009 · 3 citations*](https://md.research.elamur.ai/free/en/papers/hara-2009-effective-analysis-causes-inter-dependencies/)
120. [**Targeted Syntactic Evaluation for Grammatical Error Correction**Aomi Koyama, Masato Mita, Su-Youn Yoon, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/koyama-2025-targeted-syntactic-evaluation-grammatical-error/)
121. **[IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets](https://md.research.elamur.ai/free/en/papers/taylor-2018-iiidyt-semeval-2018-task-3/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Edison Marrese-Taylor, Suzana Ilic, Jorge Balazs, et al.*2018 · 3 citations*
122. **[An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via Surprisal](https://md.research.elamur.ai/free/en/papers/yoshida-2026-existence-proof-neural-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ryo Yoshida, Shinnosuke Isono, Taiga Someya, et al.*2026 · 1 citation*
123. **[Automatic Detection of Metaphorical Expressions in Classical Japanese Using WLSP-Enhanced BERT](https://md.research.elamur.ai/free/en/papers/zhu-2026-automatic-detection-metaphorical-expressions-classical/) [Workshop on Language Technologies for Historical and Ancient Languages @ LREC](https://md.research.elamur.ai/free/en/venues/lt4hala/)**Hang Zhu, Mitoki Ohara, Rei Kikuchi, et al.*2026 · 1 citation*
124. **[Annotating Factive Verbs](https://md.research.elamur.ai/free/en/papers/ii-2012-annotating-factive-verbs/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Alvin Grissom II, Yusuke Miyao*2012*
125. [**Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM Pretraining**Hiroshi Matsuda, Masayuki Asahara*2026*](https://md.research.elamur.ai/free/en/papers/matsuda-2026-probing-dynamics-syntactic-ability-acquisition/)
126. **[Rethinking the Relationship between the Power Law and Hierarchical Structures](https://md.research.elamur.ai/free/en/papers/nakaishi-2026-rethinking-relationship-between-power-law/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Nakaishi, Ryo Yoshida, Kohei Kajikawa, et al.*2026*
127. **[DialogueSidon: Recovering Full-Duplex Dialogue Tracks from In-the-Wild Dialogue Audio](https://md.research.elamur.ai/free/en/papers/nakata-2026-dialoguesidon-recovering-full-duplex-dialogue/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Wataru Nakata, Yuki Saito, Kazuki Yamauchi, et al.*2026*
128. **[Features for Detecting Hedge Cues](https://md.research.elamur.ai/free/en/papers/shimizu-2010-features-detecting-hedge-cues/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Nobuyuki Shimizu, Hiroshi Nakagawa*2010*
129. [**A Zipfian Analysis of Visual Token Distributions for AI-Generated Images Proceedings of the 4th Workshop on Advances in Language and Vision Research (ALVR)**Andrew Shin*2026*](https://md.research.elamur.ai/free/en/papers/shin-2026-zipfian-analysis-visual-token-distributions/)
130. **[SearchLLM: Detecting LLM Paraphrased Text by Measuring the Similarity with Regeneration of the Candidate Source via Search Engine](https://md.research.elamur.ai/free/en/papers/son-2026-searchllm-detecting-llm-paraphrased-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hoang-Quoc Nguyen-Son, Minh-Son Dao, Koji Zettsu*2026*
131. **[From Felt Sense to Words: Construction and Analysis of a Focusing Dialogue Dataset for Verbalization](https://md.research.elamur.ai/free/en/papers/tsunomori-2026-felt-sense-words-construction-analysis/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Yuiko Tsunomori, Yuya Chiba, Yosuke Koshikawa*2026*
132. **[PrePPER: A Preference Pattern-based Profiling Framework for Explainable Recommendation](https://md.research.elamur.ai/free/en/papers/usumi-2026-prepper-preference-pattern-based-profiling/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Taisuke Usumi, Akiko Masaki, Sanae Muramatsu, et al.*2026*
133. [**Beyond BLEU: Linguistic Invisibility and Interactional Repair Sequence in End-to-End Sign Language Translation Proceedings of the LREC 2026 12th Workshop on the Representation and Processing of Sign Languages: Language in Motion**Zirui Wang, Mayumi Bono*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-beyond-bleu-linguistic-invisibility-interactional/)

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