---
title: "Japan — works"
description: "Works of Japan: 143 in our library · page 1 of 2, the most cited first."
canonical: "https://research.elamur.ai/free/en/countries/japan/works/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/countries/japan/works/)

[home](https://md.research.elamur.ai/free/en/) / [countries](https://md.research.elamur.ai/free/en/countries/) / [Japan](https://md.research.elamur.ai/free/en/countries/japan/) / works

# Works of Japan

143 · page 1 of 2 · the most cited first · [← Japan](https://md.research.elamur.ai/free/en/countries/japan/)

**1** [2](https://md.research.elamur.ai/free/en/countries/japan/works/page/2/) [next →](https://md.research.elamur.ai/free/en/countries/japan/works/page/2/)

1. [**SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing**Taku Kudo, John Richardson*2018 · 4,461 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2018-sentencepiece-simple-language-independent-subword/)
2. [**Named Entity Recognition with Bidirectional LSTM-CNNs**Jason P. C. Chiu, Eric Nichols*2015 · 2,276 citations*](https://md.research.elamur.ai/free/en/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
3. [**End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures**Makoto Miwa, Mohit Bansal*2016 · 1,596 citations*](https://md.research.elamur.ai/free/en/papers/miwa-2016-end-end-relation-extraction-lstms/)
4. [**Multiword Expressions: A Pain in the Neck for NLP**Ivan A. Sag, Timothy Baldwin, Francis Bond, et al.*2002 · 1,497 citations*](https://md.research.elamur.ai/free/en/papers/sag-2002-multiword-expressions-pain-neck-nlp/)
5. [**brat: a Web-based Tool for NLP-Assisted Text Annotation**Pontus Stenetorp, Sampo Pyysalo, Goran Topić, et al.*2012 · 1,368 citations*](https://md.research.elamur.ai/free/en/papers/stenetorp-2012-brat-web-based-tool-nlp/)
6. [**Statistical Dependency Analysis with Support Vector Machines**Hiroyasu Yamada, Yuji Matsumoto*2003 · 878 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2003-statistical-dependency-analysis-support-vector/)
7. [**Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations**Sosuke Kobayashi*2018 · 804 citations*](https://md.research.elamur.ai/free/en/papers/kobayashi-2018-contextual-augmentation-data-augmentation-words/)
8. [**Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps**Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, et al.*2020 · 735 citations*](https://md.research.elamur.ai/free/en/papers/ho-2020-constructing-multi-hop-qa-dataset/)
9. [**Overview of BioNLP'09 Shared Task on Event Extraction**Jin-Dong Kim, Tomoko Ohta, Sampo Pyysalo, et al.*2009 · 735 citations*](https://md.research.elamur.ai/free/en/papers/kim-2009-overview-bionlp-09-shared-task/)
10. [**Introduction to the Bio-entity Recognition Task at JNLPBA**Nigel Collier, Tomoko Ohta, Yoshimasa Tsuruoka, et al.*2004 · 731 citations*](https://md.research.elamur.ai/free/en/papers/collier-2004-introduction-bio-entity-recognition-task/)
11. [**Findings of the 2017 Conference on Machine Translation (WMT17)**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2017 · 685 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2017-findings-2017-conference-machine-translation/)
12. [**A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks**Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, et al.*2016 · 666 citations*](https://md.research.elamur.ai/free/en/papers/hashimoto-2016-joint-many-task-model-growing/)
13. [**Chunking with Support Vector Machines**Taku Kudo, Yuji Matsumoto*2001 · 647 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2001-chunking-support-vector-machines/)
14. [**The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages**Jan Hajič, Massimiliano Ciaramita, Richard Johansson, et al.*2009 · 631 citations*](https://md.research.elamur.ai/free/en/papers/hajic-2009-conll-2009-shared-task-syntactic/)
15. [**How Powerful are Graph Neural Networks?**Keyulu Xu, Weihua Hu, Jure Leskovec, et al.*2018 · 591 citations*](https://md.research.elamur.ai/free/en/papers/xu-2018-powerful-graph-neural-networks/)
16. [**Results of the WNUT2017 Shared Task on Novel and Emerging Entity Recognition**Leon Derczynski, Eric Nichols, Marieke van Erp, et al.*2017 · 534 citations*](https://md.research.elamur.ai/free/en/papers/derczynski-2017-results-wnut2017-shared-task-novel/)
17. [**Discovering Relations among Named Entities from Large Corpora**Takaaki Hasegawa, Satoshi Sekine, Ralph Grishman*2004 · 486 citations*](https://md.research.elamur.ai/free/en/papers/hasegawa-2004-discovering-relations-among-named-entities/)
18. [**Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval**Xiaodong Liu, Jianfeng Gao, Xiaodong He, et al.*2015 · 463 citations*](https://md.research.elamur.ai/free/en/papers/liu-2015-representation-learning-multi-task-deep/)
19. [**Automatic Evaluation of Translation Quality for Distant Language Pairs**Hideki Isozaki, Tsutomu Hirao, Kevin Duh, et al.*2010 · 461 citations*](https://md.research.elamur.ai/free/en/papers/isozaki-2010-automatic-evaluation-translation-quality-distant/)
20. [**Modeling Joint Entity and Relation Extraction with Table Representation**Makoto Miwa, Yutaka Sasaki*2014 · 443 citations*](https://md.research.elamur.ai/free/en/papers/miwa-2014-modeling-joint-entity-relation-extraction/)
21. [**MasakhaNER: Named Entity Recognition for African Languages**David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, et al.*2021 · 429 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2021-masakhaner-named-entity-recognition-african/)
22. [**Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2016 · 427 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2016-joint-learning-embedding-words-entities/)
23. [**Adversarial Training Methods for Semi-Supervised Text Classification**Takeru Miyato, Andrew M. Dai, Ian Goodfellow*2016 · 416 citations*](https://md.research.elamur.ai/free/en/papers/miyato-2016-adversarial-training-methods-semi-supervised/)
24. [**Findings of the 2020 Conference on Machine Translation (WMT20)**Loïc Barrault, Magdalena Biesialska, Ondřej Bojar, et al.*2020 · 401 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2020-findings-2020-conference-machine-translation/)
25. [**A Neural Layered Model for Nested Named Entity Recognition**Meizhi Ju, Makoto Miwa, Sophia Ananiadou*2018 · 378 citations*](https://md.research.elamur.ai/free/en/papers/ju-2018-neural-layered-model-nested-named/)
26. [**Probabilistic CFG with Latent Annotations**Takuya Matsuzaki, Yusuke Miyao, Jun'ichi Tsujii*2005 · 375 citations*](https://md.research.elamur.ai/free/en/papers/matsuzaki-2005-probabilistic-cfg-latent-annotations/)
27. [**Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis**Graham Neubig, Yosuke Nakata, Shinsuke Mori*2011 · 368 citations*](https://md.research.elamur.ai/free/en/papers/neubig-2011-pointwise-prediction-robust-adaptable-japanese/)
28. [**HILDA: A Discourse Parser Using Support Vector Machine Classification**Hugo Hernault, Helmut Prendinger, David A. du Verle, et al.*2010 · 353 citations*](https://md.research.elamur.ai/free/en/papers/hernault-2010-hilda-discourse-parser-support-vector/)
29. [**Toward a Broad-coverage Bilingual Corpus for Speech Translation of Travel Conversations in the Real World**Toshiyuki Takezawa, Eiichiro Sumita, Fumiaki Sugaya, et al.*2002 · 328 citations*](https://md.research.elamur.ai/free/en/papers/takezawa-2002-broad-coverage-bilingual-corpus-speech/)
30. [**Controlling Output Length in Neural Encoder-Decoders**Yuta Kikuchi, Graham Neubig, Ryohei Sasano, et al.*2016 · 323 citations*](https://md.research.elamur.ai/free/en/papers/kikuchi-2016-controlling-output-length-neural-encoder/)
31. [**An Empirical Model of Multiword Expression Decomposability**Timothy Baldwin, Colin Bannard, Takaaki Tanaka, et al.*2003 · 319 citations*](https://md.research.elamur.ai/free/en/papers/baldwin-2003-empirical-model-multiword-expression-decomposability/)
32. [**Entailment above the word level in distributional semantics**Marco Baroni, Raffaella Bernardi, Ngoc-Quynh Do, et al.*2012 · 318 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2012-entailment-above-word-level-distributional/)
33. [**An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation**Chenhui Chu, Raj Dabre, Sadao Kurohashi*2017 · 316 citations*](https://md.research.elamur.ai/free/en/papers/chu-2017-empirical-comparison-domain-adaptation-methods/)
34. [**Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't.**Anna Gladkova, Aleksandr Drozd, Satoshi Matsuoka*2016 · 311 citations*](https://md.research.elamur.ai/free/en/papers/gladkova-2016-analogy-based-detection-morphological-semantic/)
35. [**Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles**Kenji Sagae, Jun'ichi Tsujii*2007 · 311 citations*](https://md.research.elamur.ai/free/en/papers/sagae-2007-dependency-parsing-domain-adaptation-lr/)
36. [**Incorporating Discrete Translation Lexicons into Neural Machine Translation**Philip Arthur, Graham Neubig, Satoshi Nakamura*2016 · 298 citations*](https://md.research.elamur.ai/free/en/papers/arthur-2016-incorporating-discrete-translation-lexicons-into/)
37. [**Neural language models as psycholinguistic subjects: Representations of syntactic state**Richard Futrell, Ethan Wilcox, Takashi Morita, et al.*2019 · 291 citations*](https://md.research.elamur.ai/free/en/papers/futrell-2019-neural-language-models-as-psycholinguistic/)
38. [**Is ChatGPT a Good NLG Evaluator? A Preliminary Study**Jiaan Wang, Yunlong Liang, Fandong Meng, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-chatgpt-good-nlg-evaluator-preliminary/)
39. [**Feature Forest Models for Probabilistic HPSG Parsing**Yusuke Miyao, Jun'ichi Tsujii*2008 · 279 citations*](https://md.research.elamur.ai/free/en/papers/miyao-2008-feature-forest-models-probabilistic-hpsg/)
40. [**What do RNN Language Models Learn about Filler-Gap Dependencies?**Ethan Wilcox, Roger Levy, Takashi Morita, et al.*2018 · 276 citations*](https://md.research.elamur.ai/free/en/papers/wilcox-2018-rnn-language-models-learn-about/)
41. [**A Comparison of Pivot Methods for Phrase-Based Statistical Machine Translation**Masao Utiyama, Hitoshi Isahara*2007 · 263 citations*](https://md.research.elamur.ai/free/en/papers/utiyama-2007-comparison-pivot-methods-phrase-based/)
42. [**GPT-RE: In-context Learning for Relation Extraction using Large Language Models**Zhen Wan, Fei Cheng, Zhuoyuan Mao, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-gpt-re-context-learning-relation/)
43. [**Personality Traits in Large Language Models**Greg Serapio-Garcia, Mustafa Safdari, Clement Crepy, et al.*2023 · 251 citations*](https://md.research.elamur.ai/free/en/papers/serapio-garcia-2023-personality-traits-large-language-models/)
44. [**ASPEC: Asian Scientific Paper Excerpt Corpus**Toshiaki Nakazawa, Manabu Yaguchi, Kiyotaka Uchimoto, et al.*2016 · 245 citations*](https://md.research.elamur.ai/free/en/papers/nakazawa-2016-aspec-asian-scientific-paper-excerpt/)
45. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
46. [**Learning to Parse and Translate Improves Neural Machine Translation**Akiko Eriguchi, Yoshimasa Tsuruoka, Kyunghyun Cho*2017 · 214 citations*](https://md.research.elamur.ai/free/en/papers/eriguchi-2017-learning-parse-translate-improves-neural/)
47. [**Towards an ISO Standard for Dialogue Act Annotation**Harry Bunt, Jan Alexandersson, Jean Carletta, et al.*2010 · 210 citations*](https://md.research.elamur.ai/free/en/papers/bunt-2010-iso-standard-dialogue-act-annotation/)
48. [**Tense and Aspect Error Correction for ESL Learners Using Global Context**Toshikazu Tajiri, Mamoru Komachi, Yuji Matsumoto*2012 · 206 citations*](https://md.research.elamur.ai/free/en/papers/tajiri-2012-tense-aspect-error-correction-esl/)
49. [**ISO 24617-2: A semantically-based standard for dialogue annotation**Harry Bunt, Jan Alexandersson, Jae-Woong Choe, et al.*2012 · 182 citations*](https://md.research.elamur.ai/free/en/papers/bunt-2012-iso-24617-2-semantically-based/)
50. [**Findings of the IWSLT 2022 Evaluation Campaign**Antonios Anastasopoulos, Loïc Barrault, Luisa Bentivogli, et al.*2022 · 177 citations*](https://md.research.elamur.ai/free/en/papers/anastasopoulos-2022-findings-iwslt-2022-evaluation-campaign/)
51. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
52. [**Debiasing Pre-trained Contextualised Embeddings**Masahiro Kaneko, Danushka Bollegala*2021 · 174 citations*](https://md.research.elamur.ai/free/en/papers/kaneko-2021-debiasing-pre-trained-contextualised-embeddings/)
53. [**Predicting Discourse Connectives for Implicit Discourse Relation Recognition**Zhi-Min Zhou, Yu Xu, Zheng-Yu Niu, et al.*2010 · 163 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2010-predicting-discourse-connectives-implicit-discourse/)
54. [**Annotating a Japanese Text Corpus with Predicate-Argument and Coreference Relations**Ryu Iida, Mamoru Komachi, Kentaro Inui, et al.*2007 · 162 citations*](https://md.research.elamur.ai/free/en/papers/iida-2007-annotating-japanese-text-corpus-predicate/)
55. [**Abstract Generation Based on Rhetorical Structure Extraction**Kenji Ono, Kazuo Sumita, Seiji Miike*1994 · 159 citations*](https://md.research.elamur.ai/free/en/papers/ono-1994-abstract-generation-based-rhetorical-structure/)
56. [**A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation**David Ifeoluwa Adelani, Jesujoba Oluwadara Alabi, Angela Fan, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2022-few-thousand-translations-go-long/)
57. [**FINDINGS OF THE IWSLT 2023 EVALUATION CAMPAIGN**Milind Agarwal, Sweta Agrawal, Antonios Anastasopoulos, et al.*2023 · 153 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-findings-iwslt-2023-evaluation-campaign/)
58. [**Probabilistic Disambiguation Models for Wide-Coverage HPSG Parsing**Yusuke Miyao, Jun'ichi Tsujii*2005 · 153 citations*](https://md.research.elamur.ai/free/en/papers/miyao-2005-probabilistic-disambiguation-models-wide-coverage/)
59. [**MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition**David Ifeoluwa Adelani, Graham Neubig, Sebastian Ruder, et al.*2022 · 150 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2022-masakhaner-2-0-africa-centric/)
60. [**Deep contextualized word representations for detecting sarcasm and irony**Suzana Ilić, Edison Marrese-Taylor, Jorge Balazs, et al.*2018 · 141 citations*](https://md.research.elamur.ai/free/en/papers/ilic-2018-deep-contextualized-word-representations-detecting/)
61. [**RUSE: Regressor Using Sentence Embeddings for Automatic Machine Translation Evaluation**Hiroki Shimanaka, Tomoyuki Kajiwara, Mamoru Komachi*2018 · 140 citations*](https://md.research.elamur.ai/free/en/papers/shimanaka-2018-ruse-regressor-sentence-embeddings-automatic/)
62. [**A Novel Discourse Parser Based on Support Vector Machine Classification**David duVerle, Helmut Prendinger*2009 · 135 citations*](https://md.research.elamur.ai/free/en/papers/duverle-2009-novel-discourse-parser-based-support/)
63. [**Task-oriented Evaluation of Syntactic Parsers and Their Representations**Yusuke Miyao, Rune Sætre, Kenji Sagae, et al.*2008 · 129 citations*](https://md.research.elamur.ai/free/en/papers/miyao-2008-task-oriented-evaluation-syntactic-parsers/)
64. [**Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment**Masatoshi Tsuchiya*2018 · 125 citations*](https://md.research.elamur.ai/free/en/papers/tsuchiya-2018-performance-impact-caused-hidden-bias/)
65. [**Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities**Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2024-continual-pre-training-cross-lingual/)
66. [**Dependency-based Discourse Parser for Single-Document Summarization**Yasuhisa Yoshida, Jun Suzuki, Tsutomu Hirao, et al.*2014 · 113 citations*](https://md.research.elamur.ai/free/en/papers/yoshida-2014-dependency-based-discourse-parser-single/)
67. [**A Cross-Lingual ILP Solution to Zero Anaphora Resolution**Ryu Iida, Massimo Poesio*2011 · 110 citations*](https://md.research.elamur.ai/free/en/papers/iida-2011-cross-lingual-ilp-solution-zero/)
68. [**A Discriminative Approach to Japanese Zero Anaphora Resolution with Large-scale Lexicalized Case Frames**Ryohei Sasano, Sadao Kurohashi*2011 · 91 citations*](https://md.research.elamur.ai/free/en/papers/sasano-2011-discriminative-approach-japanese-zero-anaphora/)
69. [**JGLUE: Japanese General Language Understanding Evaluation**Kentaro Kurihara, Daisuke Kawahara, Tomohide Shibata*2022 · 90 citations*](https://md.research.elamur.ai/free/en/papers/kurihara-2022-jglue-japanese-general-language-understanding/)
70. [**Exploiting Syntactic Patterns as Clues in Zero-Anaphora Resolution**Ryu Iida, Kentaro Inui, Yuji Matsumoto*2006 · 84 citations*](https://md.research.elamur.ai/free/en/papers/iida-2006-exploiting-syntactic-patterns-as-clues/)
71. [**Discriminative Approach to Predicate-Argument Structure Analysis with Zero-Anaphora Resolution**Kenji Imamura, Kuniko Saito, Tomoko Izumi*2009 · 77 citations*](https://md.research.elamur.ai/free/en/papers/imamura-2009-discriminative-approach-predicate-argument-structure/)
72. [**RNNs as psycholinguistic subjects: Syntactic state and grammatical dependency**Richard Futrell, Ethan Wilcox, Takashi Morita, et al.*2018 · 75 citations*](https://md.research.elamur.ai/free/en/papers/futrell-2018-rnns-psycholinguistic-subjects-syntactic-state/)
73. [**Findings of the WMT25 General Machine Translation Shared Task: Time to Stop Evaluating on Easy Test Sets**Tom Kocmi, Ekaterina Artemova, Eleftherios Avramidis, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2025-findings-wmt25-general-machine-translation/)
74. [**A Unified Theory of Irony and Its Computational Formalization**Akira Utsumi*1996 · 70 citations*](https://md.research.elamur.ai/free/en/papers/utsumi-1996-unified-theory-irony-its-computational/)
75. [**Adapting BERT to Implicit Discourse Relation Classification with a Focus on Discourse Connectives**Yudai Kishimoto, Yugo Murawaki, Sadao Kurohashi*2020 · 68 citations*](https://md.research.elamur.ai/free/en/papers/kishimoto-2020-adapting-bert-implicit-discourse-relation/)
76. [**A Probabilistic Method for Analyzing Japanese Anaphora Integrating Zero Pronoun Detection and Resolution**Kazuhiro Seki, Atsushi Fujii, Tetsuya Ishikawa*2002 · 65 citations*](https://md.research.elamur.ai/free/en/papers/seki-2002-probabilistic-method-analyzing-japanese-anaphora/)
77. [**A Fully-Lexicalized Probabilistic Model for Japanese Zero Anaphora Resolution**Ryohei Sasano, Daisuke Kawahara, Sadao Kurohashi*2008 · 63 citations*](https://md.research.elamur.ai/free/en/papers/sasano-2008-fully-lexicalized-probabilistic-model-japanese/)
78. [**Anaphora Resolution of Japanese Zero Pronouns with Deictic Reference**Hiromi Nakaiwa, Satoshi Shirai*1996 · 62 citations*](https://md.research.elamur.ai/free/en/papers/nakaiwa-1996-anaphora-resolution-japanese-zero-pronouns/)
79. [**Japanese Zero Pronoun Resolution based on Ranking Rules and Machine Learning**Hideki Isozaki, Tsutomu Hirao*2003 · 57 citations*](https://md.research.elamur.ai/free/en/papers/isozaki-2003-japanese-zero-pronoun-resolution-based/)
80. [**Joint Transition-based Dependency Parsing and Disfluency Detection for Automatic Speech Recognition Texts**Masashi Yoshikawa, Hiroyuki Shindo, Yuji Matsumoto*2016 · 56 citations*](https://md.research.elamur.ai/free/en/papers/yoshikawa-2016-joint-transition-based-dependency-parsing/)
81. [**Zero Pronoun Resolution in Japanese Discourse Based on Centering Theory**Manabu Okumura, Kouji Tamura*1996 · 53 citations*](https://md.research.elamur.ai/free/en/papers/okumura-1996-zero-pronoun-resolution-japanese-discourse/)
82. [**A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension**Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuka*2010 · 52 citations*](https://md.research.elamur.ai/free/en/papers/hernault-2010-semi-supervised-approach-improve-classification/)
83. [**Intra-Sentential Subject Zero Anaphora Resolution using Multi-Column Convolutional Neural Network**Ryu Iida, Kentaro Torisawa, Jong-Hoon Oh, et al.*2016 · 51 citations*](https://md.research.elamur.ai/free/en/papers/iida-2016-intra-sentential-subject-zero-anaphora/)
84. [**Universal Dependencies Version 2 for Japanese**Masayuki Asahara, Hiroshi Kanayama, Takaaki Tanaka, et al.*2018 · 50 citations*](https://md.research.elamur.ai/free/en/papers/asahara-2018-universal-dependencies-version-2-japanese/)
85. [**Reference-based Metrics can be Replaced with Reference-less Metrics in Evaluating Grammatical Error Correction Systems**Hiroki Asano, Tomoya Mizumoto, Kentaro Inui*2017 · 49 citations*](https://md.research.elamur.ai/free/en/papers/asano-2017-reference-based-metrics-can-be/)
86. [**Interpretability for Language Learners Using Example-Based Grammatical Error Correction**Masahiro Kaneko, Sho Takase, Ayana Niwa, et al.*2022 · 47 citations*](https://md.research.elamur.ai/free/en/papers/kaneko-2022-interpretability-language-learners-example-based/)
87. [**Semantic Dependency Parsing of NomBank and PropBank: An Efficient Integrated Approach via a Large-scale Feature Selection**Hai Zhao, Wenliang Chen, Chunyu Kit*2009 · 42 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2009-semantic-dependency-parsing-nombank-propbank/)
88. [**Extractive Summarization Considering Discourse and Coreference Relations based on Heterogeneous Graph**Yin Jou Huang, Sadao Kurohashi*2021 · 41 citations*](https://md.research.elamur.ai/free/en/papers/huang-2021-extractive-summarization-considering-discourse-coreference/)
89. [**Joint Prediction of Morphosyntactic Categories for Fine-Grained Arabic Part-of-Speech Tagging Exploiting Tag Dictionary Information**Go Inoue, Hiroyuki Shindo, Yuji Matsumoto*2017 · 39 citations*](https://md.research.elamur.ai/free/en/papers/inoue-2017-joint-prediction-morphosyntactic-categories-fine/)
90. [**A Comparative Study on Generalization of Semantic Roles in FrameNet**Yuichiroh Matsubayashi, Naoaki Okazaki, Jun'ichi Tsujii*2009 · 39 citations*](https://md.research.elamur.ai/free/en/papers/matsubayashi-2009-comparative-study-generalization-semantic-roles/)
91. [**Intra-sentential Zero Anaphora Resolution using Subject Sharing Recognition**Ryu Iida, Kentaro Torisawa, Chikara Hashimoto, et al.*2015 · 38 citations*](https://md.research.elamur.ai/free/en/papers/iida-2015-intra-sentential-zero-anaphora-resolution/)
92. [**Identifying Zero Pronouns in Japanese Dialogue**Kei Yoshimoto*1988 · 35 citations*](https://md.research.elamur.ai/free/en/papers/yoshimoto-1988-identifying-zero-pronouns-japanese-dialogue/)
93. [**Construction of English MWE Dictionary and its Application to POS Tagging**Yutaro Shigeto, Ai Azuma, Sorami Hisamoto, et al.*2013 · 34 citations*](https://md.research.elamur.ai/free/en/papers/shigeto-2013-construction-english-mwe-dictionary-its/)
94. [**Zero Pronoun Resolution can Improve the Quality of J-E Translation**Hirotoshi Taira, Katsuhito Sudoh, Masaaki Nagata*2012 · 34 citations*](https://md.research.elamur.ai/free/en/papers/taira-2012-zero-pronoun-resolution-can-improve/)
95. [**Overview of BioNLP 2011 Protein Coreference Shared Task**Ngan Nguyen, Jin-Dong Kim, Jun'ichi Tsujii*2011 · 32 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2011-overview-bionlp-2011-protein-coreference/)
96. [**Using Explicit Discourse Connectives in Translation for Implicit Discourse Relation Classification**Wei Shi, Frances Yung, Raphael Rubino, et al.*2017 · 25 citations*](https://md.research.elamur.ai/free/en/papers/shi-2017-explicit-discourse-connectives-translation-implicit/)
97. [**BCCWJ-DepPara: A Syntactic Annotation Treebank on the ‘Balanced Corpus of Contemporary Written Japanese'**Masayuki Asahara, Yuji Matsumoto*2016 · 23 citations*](https://md.research.elamur.ai/free/en/papers/asahara-2016-bccwj-deppara-syntactic-annotation-treebank/)
98. [**Taking the Correction Difficulty into Account in Grammatical Error Correction Evaluation**Takumi Gotou, Ryo Nagata, Masato Mita, et al.*2020 · 23 citations*](https://md.research.elamur.ai/free/en/papers/gotou-2020-taking-correction-difficulty-into-account/)
99. [**Entity-Centric Joint Modeling of Japanese Coreference Resolution and Predicate Argument Structure Analysis**Tomohide Shibata, Sadao Kurohashi*2018 · 23 citations*](https://md.research.elamur.ai/free/en/papers/shibata-2018-entity-centric-joint-modeling-japanese/)
100. [**Dialogue Act-based Breakdown Detection in Negotiation Dialogues**Atsuki Yamaguchi, Kosui Iwasa, Katsuhide Fujita*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/yamaguchi-2021-dialogue-act-based-breakdown-detection/)

**1** [2](https://md.research.elamur.ai/free/en/countries/japan/works/page/2/) [next →](https://md.research.elamur.ai/free/en/countries/japan/works/page/2/)

- [← back to](https://md.research.elamur.ai/free/en/countries/japan/) — Japan