Publications

Type: [Japanese] [English] Chronological: [Japanese] [English]

Papers

2024

  1. Daichi Yamaguchi, Rei Miyata, Atsushi Fujita, Tomoyuki Kajiwara, and Satoshi Sato. Automatic Decomposition of Text Editing Examples into Primitive Edit Operations: Toward Analytic Evaluation of Editing Systems. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), pp. XXXX-XXXX, May, 2024. [Paper] [Slides]

2023

  1. Tomono Honda, Atsushi Fujita, Mayuka Yamamoto, and Kyo Kageura. A Scheme for Describing Differences Between Translations: Refinement of Typology and Evaluation as a Metalanguage. Interpreting and Translation Studies, Vol. 23, pp. 83-103, Dec., 2023. (in Japanese) (DOI)
  2. Mayuka Yamamoto, Atsushi Fujita, and Kyo Kageura. Refinement of a Typology of Translation Strategies for English-to-Japanese Translation Based on Actual Examples and Multi-Person Discussions. Interpreting and Translation Studies, Vol. 23, pp. 15-35, Dec., 2023. (in Japanese) (DOI)
  3. Yuto Kuroda, Atsushi Fujita, Tomoyuki Kajiwara, and Takashi Ninomiya. Unsupervised Translation Quality Estimation Exploiting Synthetic Data and Pre-trained Multilingual Encoder. arXiv:2311.05117, 10 pages, Nov., 2023. (Preprint)
  4. Haiyue Song, Raj Dabre, Chenhui Chu, Atsushi Fujita, and Sadao Kurohashi. Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Transcripts. arXiv:2311.03696, 17 pages, Nov., 2023. (Preprint)
  5. Hui Piao, Kyo Kageura, Mayuka Yamamoto, and Atsushi Fujita. Exploring a Metalanguage of Source Document Elements in Translator Training. In Proceedings of the 1st High-level Forum on Foreign Language Pedagogy, Sep., 2023. [Slides]
  6. Tomono Honda, Atsushi Fujita, Mayuka Yamamoto, and Kyo Kageura. Designing a Metalanguage of Differences Between Translations: A Case Study for English-to-Japanese Translation. In Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems (HumEval), pp. 23-34, Sep., 2023. (Paper) [Slides]
  7. Hyuga Koretaka, Tomoyuki Kajiwara, Atsushi Fujita, and Takashi Ninomiya. Mitigating Domain Mismatch in Machine Translation via Paraphrasing. In Proceedings of the 10th Workshop on Asian Translation (WAT), pp. 29-40, Sep., 2023. (Paper) [Slides]

2022

  1. Raphael Rubino and Atsushi Fujita. Quality Estimation of Machine Translation Outputs. Journal of NICT, Vol. 68, No. 2, pp. 73-81, Dec., 2022. (in Japanese) (Paper)
  2. Atsushi Fujita. Natural Language Processing Techniques for Translation. Metalanguages for Dissecting Translation Processes: Theoretical Development and Practical Applications, Chapter 16, pp. 216-236, Routledge, Jul., 2022. (Publisher) (Amazon.co.jp)
  3. Atsushi Fujita, Kikuko Tanabe, Kaemi Tanaka, and Mayuka Yamamoto. Implementing and Validating a Metalanguage of Translation Issues in Translation Education. Metalanguages for Dissecting Translation Processes: Theoretical Development and Practical Applications, Chapter 11, pp. 145-165, Routledge, Jul., 2022. (Publisher) (Amazon.co.jp)
  4. Atsushi Fujita, Kikuko Tanabe, and Chiho Toyoshima. Designing a Metalanguage of Translation Issues. Metalanguages for Dissecting Translation Processes: Theoretical Development and Practical Applications, Chapter 8, pp. 92-115, Routledge, Jul., 2022. (Publisher) (Amazon.co.jp)

2021

  1. Raphael Rubino, Atsushi Fujita, and Benjamin Marie. Error Identification for Machine Translation with Metric Embedding and Attention. In Proceedings of the 2nd Workshop on Evaluation and Comparison of NLP Systems (Eval4NLP), pp. 146-156, Nov., 2021. (Best Overall Approach Award) (Paper) (video)
  2. Raphael Rubino, Atsushi Fujita, and Benjamin Marie. NICT Kyoto Submission for the WMT'21 Quality Estimation Task: Multimetric Multilingual Pretraining for Critical Error Detection. In Proceedings of the 6th Conference on Machine Translation (WMT), pp. 941-947, Nov., 2021. (Paper)
  3. Mayuka Yamamoto, Masaru Yamada, Atsushi Fujita, Rei Miyata, and Kyo Kageura. Designing a Metalanguage of Translation Strategies for Translation Training: Demystifying the Art of Translation. In the 7th International Conference of International Association for Translation and Intercultural Studies (IATIS), Sep., 2021. [Slides]
  4. Atsushi Fujita. Attainable Text-to-Text Machine Translation vs. Translation: Issues Beyond Linguistic Processing. In Proceedings of the 18th Machine Translation Summit (MT Summit), pp. 215-230, Aug., 2021. [Paper] [Slides] (Staged PE Dataset)
  5. Raj Dabre and Atsushi Fujita. Investigating Softmax Tempering for Training Neural Machine Translation Models. In Proceedings of the 18th Machine Translation Summit (MT Summit), pp. 114-126, Aug., 2021. [Paper] [Slides]
  6. Benjamin Marie, Atsushi Fujita, and Raphael Rubino. Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers. In Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP), pp. 7297-7306, Aug., 2021. (Outstanding Paper Award) [Paper] (video) (Dataset)
  7. Benjamin Marie, Atsushi Fujita, and Raphael Rubino. Scientific Credibility of Machine Translation Research: A Meta-Evaluation of 769 Papers. arXiv:2106.15195, 10 pages, Jun., 2021. [Formal publication] (Preprint) (Dataset)
  8. Raj Dabre and Atsushi Fujita. Recurrent Stacking of Layers in Neural Networks: An Application to Neural Machine Translation. arXiv:2106.10002, 22 pages, Jun., 2021. (Preprint)
  9. Atsushi Fujita. Translation Issues Caused by Machine Translation due to a Lack of Indispensable Information. The 60th Regular Meeting of the Japan Association for Interpreting and Translation Studies, Jun., 2021. (Invited talk) (in Japanese) [Slides]
  10. Rei Miyata and Atsushi Fujita. Understanding Pre-Editing for Black-Box Neural Machine Translation. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL), pp. 1539-1550, Apr., 2021. [Paper] [Slides] [Poster]
  11. Benjamin Marie and Atsushi Fujita. Altering Parallel Data of User-Generated Texts with Zero-Shot Neural Machine Translation. Proceedings of the 27th Annual Meeting of Natural Language Processing (NLP), P1-5, pp. 128-132, Mar., 2021.
  12. Rei Miyata and Atsushi Fujita. Understanding Pre-Editing for Black-Box Neural Machine Translation. arXiv:2102.02955, 12 pages, Feb., 2021. [Formal publication] (Preprint)
  13. Benjamin Marie and Atsushi Fujita. Synthesizing Monolingual Data for Neural Machine Translation. arXiv:2101.12462, 8 pages, Feb., 2021. (Preprint)

2020

  1. Raphael Rubino, Benjamin Marie, Raj Dabre, Atsushi Fujita, Masao Utiyama, and Eiichiro Sumita. Extremely Low-Resource Neural Machine Translation for Asian Languages. Machine Translation, Vol. 34, No. 4, pp. 347-382, Dec., 2020. (Springer) (DOI)
  2. Raj Dabre and Atsushi Fujita. Combining Sequence Distillation and Transfer Learning for Efficient Low-Resource Neural Machine Translation Models. In Proceedings of the 5th Conference on Machine Translation (WMT), pp. 492-502, Nov., 2020. [Paper] (video)
  3. Benjamin Marie, Raphael Rubino, and Atsushi Fujita. Combination of Neural Machine Translation Systems at WMT20. In Proceedings of the 5th Conference on Machine Translation (WMT), pp. 230-238, Nov., 2020. (Paper) (video)
  4. Benjamin Marie and Atsushi Fujita. Synthesizing Parallel Data of User-Generated Texts with Zero-Shot Neural Machine Translation. Transactions of the Association for Computational Linguistics (TACL), Vol. 8, pp. 710-725, Nov., 2020. (MIT Press) (DOI) (video)
  5. Masaru Yamada, Mayuka Yamamoto, Nanami Onishi, Atsushi Fujita, Rei Miyata, and Kyo Kageura. Metalanguage for the Translation Process. In Proceedings of the 5th Conference on Translation in Transition: Human and Machine Intelligence (TT5), pp. 46-51, Oct., 2020. [Paper]
  6. Raj Dabre and Atsushi Fujita. Softmax Tempering for Training Neural Machine Translation Models. arXiv:2009.09372, 11 pages, Sep., 2020. [Formal publication] (Preprint)
  7. Atsushi Fujita. Recent Advances in Machine Translation and How It Differs from Translation. The 42nd Meeting of the Japanese Language Association of Korea, Sep., 2020. (Keynote talk) (in Japanese) [Slides]
  8. Raj Dabre, Raphael Rubino, and Atsushi Fujita. Balancing Cost and Benefit with Tied-Multi Transformers. In Proceedings of the 4th Workshop on Neural Generation and Translation (WNGT), pp. 24-34, Jul., 2020. [Paper] (video)
  9. Benjamin Marie, Raphael Rubino, and Atsushi Fujita. Tagged Back-translation Revisited: Why Does It Really Work? In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL), Short papers, pp. 5990-5997, Jul., 2020. [Paper] (video)
  10. Benjamin Marie and Atsushi Fujita. Iterative Training of Unsupervised Neural and Statistical Machine Translation Systems. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 19, No. 5, Article 68, 21 pages, Jun., 2020. (ACM DL) (DOI)
  11. Haiyue Song, Raj Dabre, Atsushi Fujita, and Sadao Kurohashi. Coursera Corpus Mining and Multistage Fine-Tuning for Improving Lectures Translation. In Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC), pp. 3633-3642, May, 2020. [Paper]
  12. Kenji Imamura, Atsushi Fujita, Eiichiro Sumita. Neural Machine Translation Using Multiple Back-translation Generated by Sampling. Transactions of the Japanese Society for Artificial Intelligence, Vol. 35, No. 3, Article A-JA9, pp. 1-9, May, 2020. (in Japanese) (DOI)
  13. Benjamin Marie and Atsushi Fujita. Questioning the Use of Bilingual Lexicon Induction as an Evaluation Task for Bilingual Word Embeddings. Proceedings of the 26th Annual Meeting of Natural Language Processing (NLP), P5-14, pp. 1225-1228, Mar., 2020. (Paper)
  14. Haiyue Song, Raj Dabre, Atsushi Fujita, and Sadao Kurohashi. Domain Adaptation of Neural Machine Translation through Multistage Fine-Tuning. Proceedings of the 26th Annual Meeting of Natural Language Processing (NLP), D2-3, pp. 461-464, Mar., 2020. (Paper)
  15. Raj Dabre, Raphael Rubino, and Atsushi Fujita. Balancing Cost and Benefit with Tied-Multi Transformers. arXiv:2002.08614, 10 pages, Feb., 2020. [Formal publication] (Preprint)

2019

  1. Haiyue Song, Raj Dabre, Atsushi Fujita, and Sadao Kurohashi. Coursera Corpus Mining and Multistage Fine-Tuning for Improving Lectures Translation. arXiv:1912.11739, 10 pages, Dec., 2019. [Formal publication] (Preprint)
  2. Raj Dabre, Raphael Rubino, and Atsushi Fujita. Balancing Cost and Benefit with Tied-Multi Transformers. Open review for ICLR 2020, 12 pages, Dec., 2019. [Formal publication] (Preprint)
  3. Raj Dabre, Atsushi Fujita, and Chenhui Chu. Exploiting Multilingualism through Multistage Fine-Tuning for Low-Resource Neural Machine Translation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), Short papers, pp. 1410-1416, Nov., 2019. [Paper] [Poster]
  4. Benjamin Marie, Hour Kaing, Aye Myat Mon, Chenchen Ding, Atsushi Fujita, Masao Utiyama, and Eiichiro Sumita. Supervised and Unsupervised Machine Translation for Myanmar-English and Khmer-English. In Proceedings of the 6th Workshop on Asian Translation (WAT), pp. 68-75, Nov., 2019. (Paper)
  5. Atsushi Fujita, Masaru Yamada, and Kyo Kageura. Revisiting Human Translation for the Next Generation of MT beyond "Language" Processing. Game Changer Innovation Contest, Translation Automation User Society (TAUS) Asia Conference & Exhibits, Oct., 2019.
  6. Raj Dabre and Atsushi Fujita. Multi-Layer Softmaxing during Training Neural Machine Translation for Flexible Decoding with Fewer Layers. arXiv:1908.10118, 7 pages, Aug., 2019. [Formal publication] (Preprint)
  7. Aizhan Imankulova, Raj Dabre, Atsushi Fujita, and Kenji Imamura. Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation. In Proceedings of the 17th Machine Translation Summit (MT Summit), pp. 128-139, Aug., 2019. [Paper] [Slides] (Dataset)
  8. Benjamin Marie, Raj Dabre, and Atsushi Fujita. NICT's Machine Translation Systems for the WMT19 Similar Language Translation Task. In Proceedings of the 4th Conference on Machine Translation (WMT), Volume 3: Shared task papers, pp. 208-212, Aug., 2019. (Paper)
  9. Benjamin Marie, Haipeng Sun, Rui Wang, Kehai Chen, Atsushi Fujita, Masao Utiyama, and Eiichiro Sumita. NICT's Unsupervised Neural and Statistical Machine Translation System for WMT19 News Translation Task. In Proceedings of the 4th Conference on Machine Translation (WMT), Volume 2: Shared task papers, pp. 294-301, Aug., 2019. (Paper)
  10. Raj Dabre, Kehai Chen, Benjamin Marie, Rui Wang, Atsushi Fujita, Masao Utiyama, and Eiichiro Sumita. NICT's Supervised Neural Machine Translation Systems for the WMT19 News Translation Task. In Proceedings of the 4th Conference on Machine Translation (WMT), Volume 2: Shared task papers, pp. 168-174, Aug., 2019. (Paper)
  11. Benjamin Marie and Atsushi Fujita. Unsupervised Joint Training of Bilingual Word Embeddings. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), Short papers, pp. 3224-3230, Jul., 2019. [Paper] [Poster]
  12. Aizhan Imankulova, Raj Dabre, Atsushi Fujita, and Kenji Imamura. Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation. arXiv:1907.03060, 12 pages, Jul., 2019. [Formal publication] (Preprint) (Dataset)
  13. Benjamin Marie and Atsushi Fujita. Unsupervised Extraction of Partial Translations for Neural Machine Translation. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), pp. 3834-3844, Jun., 2019. [Paper] [Poster]
  14. Raj Dabre and Atsushi Fujita. Recurrent Stacking of Layers for Compact Neural Machine Translation Models. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), pp. 6292-6299, Jan.-Feb., 2019. [Paper] [Poster]

2018

  1. Benjamin Marie, Atsushi Fujita, and Eiichiro Sumita. Combination of Statistical and Neural Machine Translation for Myanmar-English. In Proceedings of the 5th Workshop on Asian Translation (WAT), pp. 975-980, Dec., 2018. (Paper)
  2. Raj Dabre, Anoop Kunchukuttan, Atsushi Fujita, and Eiichiro Sumita. NICT's Participation in WAT 2018: Approaches Using Multilingualism and Recurrently Stacked Layers. In Proceedings of the 5th Workshop on Asian Translation (WAT), pp. 952-960, Dec., 2018. (Paper)
  3. Benjamin Marie, Rui Wang, Atsushi Fujita, Masao Utiyama, and Eiichiro Sumita. NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task. In Proceedings of the 3rd Conference on Machine Translation (WMT), Volume 2: Shared task papers, pp. 449-455, Oct.-Nov., 2018. (Paper) [Poster]
  4. Benjamin Marie and Atsushi Fujita. Unsupervised Neural Machine Translation Initialized by Unsupervised Statistical Machine Translation. arXiv:1810.12703, 13 pages, Oct., 2018. [Formal publication] (Preprint)
  5. Rui Wang, Benjamin Marie, Masao Utiyama, Atsushi Fujita, and Eiichiro Sumita. NICT's Machine Translation Systems for CWMT-2018 Translation Task. In Proceedings of the 14th China Workshop on Machine Translation, Oct., 2018.
  6. Benjamin Marie, Rui Wang, Atsushi Fujita, Masao Utiyama, and Eiichiro Sumita. NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task. arXiv:1809.07037, 7 pages, Sep., 2018. [Formal publication] (Preprint)
  7. Atsushi Fujita. Machine Translation: What Are Possible and What Cannot Be Possible. Special Symposium "Technologies in Translation", The 19th Annual Meeting of the Japan Association for Interpreting and Translation Studies, Sep., 2018. (Panelist) (in Japanese) [Slides]
  8. Raj Dabre and Atsushi Fujita. Recurrent Stacking of Layers for Compact Neural Machine Translation Models. arXiv:1807.05353, 6 pages, Jul., 2018. [Formal publication] (Preprint)
  9. Kenji Imamura, Atsushi Fujita, and Eiichiro Sumita. Enhancement of Encoder and Attention Using Target Monolingual Corpora in Neural Machine Translation. In Proceedings of the 2nd Workshop on Neural Machine Translation and Generation (WNMT), pp. 55-63, Jul., 2018. (Paper)
  10. Benjamin Marie and Atsushi Fujita. A Smorgasbord of Features to Combine Phrase-Based and Neural Machine Translation. In Proceedings of the 13th Biennial Conference of the Association for Machine Translation in the Americas (AMTA), pp. 111-124, Mar., 2018. [Paper]
  11. Benjamin Marie and Atsushi Fujita. Phrase Table Induction Using Monolingual Data for Low-Resource Statistical Machine Translation. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 17, No. 3, Article 16, 25 pages, Feb., 2018. (ACM DL) (DOI)
  12. Atsushi Fujita and Pierre Isabelle. Expanding Paraphrase Lexicons by Exploiting Generalities. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), Vol. 17, No. 2, Article 13, 36 pages, Jan., 2018. (ACM DL) (DOI) [Lexpanded PPDB]

2017

  1. Nanami Onishi, Masaru Yamada, Atsushi Fujita, and Kyo Kageura. Causes of Mistranslations Made by Student Translators: Investigation into X3 in the MNH-TT Revision Category through Retrospective Interviews. Invitation to Interpreting and Translation Studies, Vol. 18, pp. 88-106, Dec., 2017. (in Japanese) (Paper)
  2. Rei Miyata and Atsushi Fujita. Investigating the Effectiveness of Pre-Editing Strategy and the Diversity of Pre-Edit Operations for Better Use of Machine Translation. Invitation to Interpreting and Translation Studies, Vol. 18, pp. 53-72, Dec., 2017. (in Japanese) (Paper)
  3. Tomoyuki Kajiwara and Atsushi Fujita. Semantic Features Based on Word Alignments for Estimating Quality of Text Simplification. In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP), Vol. 2, Short papers, pp. 109-115, Nov., 2017. [Paper] [Poster]
  4. Atsushi Fujita and Eiichiro Sumita. Japanese to English/Chienese/Korean Datasets for Translation Quality Estimation and Automatic Post-Editing. In Proceedings of the 4th Workshop on Asian Translation (WAT), pp. 79-88, Nov., 2017. [Paper] [Slides] [NICT QE/APE Dataset]
  5. Benjamin Marie and Atsushi Fujita. Phrase Table Induction Using In-Domain Monolingual Data for Domain Adaptation in Statistical Machine Translation. Transactions of the Association for Computational Linguistics (TACL), Vol. 5, pp. 487-500, Nov., 2017. (MIT Press) (DOI)
  6. Atsushi Fujita. Social Demonstration of Multilingual Speech Translation Technologies: Overview of the National Project in Japan and R&D at NICT. In Proceedings of the 18th Annual Meeting of the Japan Association for Interpreting and Translation Studies, p. 20, Sep., 2017. (Invited talk) (in Japanese) [Slides]
  7. Lemao Liu, Atsushi Fujita, Masao Utiyama, Andrew Finch, and Eiichiro Sumita. Translation Quality Estimation Using Only Bilingual Corpora. IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), Vol. 25, No. 9, pp. 1762-1772, Sep., 2017. (DOI)
  8. Mio Tsubakimoto, Atsuko Tominaga, Atsushi Fujita, and Wakako Kashino. Cluster Analysis of Learners Based on Their Perception of Writing Aids. In Proceedings of the 11th International Conference on Cognitive Science (ICCS), Sep., 2017. [Poster]
  9. Benjamin Marie and Atsushi Fujita. Efficient Extraction of Pseudo-Parallel Sentences from Raw Monolingual Data Using Word Embeddings. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL), Short papers, pp. 392-398, Jul.-Aug., 2017. [Paper] [Poster]
  10. Atsushi Fujita. Natural Language Generation. In Encyclopedia of Artificial Intelligence, Section 8.28, pp. 662-664, Kyoritsu Shuppan Co., Ltd., Jul., 2017. (in Japanese) (Amazon.co.jp)
  11. Atsushi Fujita. Paraphrasing Technology. In Encyclopedia of Artificial Intelligence, Section 8.21, pp. 646-649, Kyoritsu Shuppan Co., Ltd., Jul., 2017. (in Japanese) (Amazon.co.jp)
  12. Atsushi Fujita. Language Technologies for Exploiting Machine Translation Systems. The 5th Meeting of SIG Translation and Interpreting Technologies, The Japan Association for Interpreting and Translation Studies, Jul., 2017. (Invited talk) (in Japanese) [Slides]
  13. Rei Miyata and Atsushi Fujita. Dissecting Human Pre-Editing toward Better Use of Off-the-Shelf Machine Translation Systems. In Proceedings of the 20th Annual Conference of the European Association for Machine Translation (EAMT), User studies papers, pp. 54-59, May, 2017. [Paper] [Poster]
  14. Kyo Kageura, Takeshi Abekawa, Martin Thomas, Atsushi Fujita, Anthony Hartley, Kikuko Tanabe, Chiho Toyoshima, and Masao Utiyama. The Role of Scaffolding and Visualisation in Supporting Collaborative Translator Training: The Case of Minna no Hon'yaku for Translator Training (MNH-TT). In Proceedings of the 1st World Congress on Translation Studies: Workshop on the Evolution of the Translation Profession and New Collaborative Practices, Apr., 2017.
  15. Atsushi Fujita, Kikuko Tanabe, Chiho Toyoshima, Mayuka Yamamoto, Kyo Kageura, and Anthony Hartley. Consistent Classification of Translation Revisions: A Case Study of English-Japanese Student Translations. In Proceedings of the 11th Linguistic Annotation Workshop (LAW), pp. 57-66, Apr., 2017. [Paper] [Poster]

2016

  1. Masaru Fuji, Atsushi Fujita, Masao Utiyama, Eiichiro Sumita, Yuji Matsumoto. Patent Claim Translation Based on Sublanguage-specific Sentence Structure. Journal of Natural Language Processing, Vol. 23, No. 5, pp. 407-435, Dec., 2016. (in Japanese) (DOI)
  2. Chiho Toyoshima, Atsushi Fujita, Kikuko Tanabe, Kyo Kageura, Anthony Hartley. Analysis of Error Patterns of Translation Students based on Revision Categories. Invitation to Interpreting and Translation Studies, Vol. 16, pp. 47-65, Dec., 2016. (in Japanese) (Paper)
  3. Kyo Kageura, Martin Thomas, Anthony Hartley, Masao Utiyama, Atsushi Fujita, Kikuko Tanabe, and Chiho Toyoshima. Supporting Collaborative Translator Training: Online Platform, Scaffolding and NLP. In Proceedings of the 14th Annual Workshop of the Australasian Language Technology Association (ALTA), Dec., 2016.

2015

  1. Atsushi Fujita. Paraphrasing Technology: Dealing with Linguistic Expressions Having the Same Meaning. IPSJ Magazine, Vol. 57, No. 1, pp. 18-19, Dec., 2015. (in Japanese)
  2. Masaru Fuji, Atsushi Fujita, Masao Utiyama, Eiichiro Sumita, and Yuji Matsumoto. Patent Claim Translation based on Sublanguage-specific Sentence Structure. In Proceedings of the 15th Machine Translation Summit (MT Summit), pp. 1-16, Oct.-Nov., 2015. (Paper)
  3. Atsushi Fujita and Pierre Isabelle. Expanding Paraphrase Lexicons by Exploiting Lexical Variants. In Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), pp. 630-640, Jun., 2015. [Paper] [Poster] [Lexpanded PPDB]

2014

  1. Yuichiroh Matsubayashi, Ryu Iida, Ryohei Sasano, Hikaru Yokono, Suguru Matsuyoshi, Atsushi Fujita, Yusuke Miyao, and Kentaro Inui. Issues on Annotation Guidelines for Japanese Predicate-Argument Structures. Journal of Natural Language Processing, Vol. 21, No. 2, pp. 333-378, Apr., 2014. (in Japanese) (FY2014 Association for Natural Language Processing, Best Paper Award) (DOI)

2013

  1. Atsushi Fujita. A Consideration on the Methodology for Evaluating Large-scale Paraphrase Lexicons. In Information Processing Society of Japan SIG Notes, NL-214-21, 8 pages, Nov., 2013. [Paper]
  2. Atsushi Fujita. Recent advances in Automatic Paraphrasing: Typology, Knowledge Acquisition, and Applications. Information Processing Society of Japan SIG Notes, NL-212-6, p. 1, Jul., 2013. (Invited talk) (in Japanese) [Paper] [Slides]
  3. Atsushi Fujita and Marine Carpuat. FUN-NRC: Paraphrase-augmented Phrase-based SMT Systems for NTCIR-10 PatentMT. In Proceedings of the 10th NTCIR Conference on Evaluation of Information Access Technologies, pp. 327-334, Jun., 2013. [Paper] [Slides] [Poster]

2012

  1. Michel Simard and Atsushi Fujita. A Poor Man's Translation Memory Using Machine Translation Evaluation Metrics. In Proceedings of the 10th Biennial Conference of the Association for Machine Translation in the Americas (AMTA), 10 pages, Oct., 2012. [Paper] [Poster]
  2. Atsushi Fujita, Pierre Isabelle, and Roland Kuhn. Enlarging Paraphrase Collections through Generalization and Instantiation. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL), pp. 631-642, Jul., 2012. [Paper] [Poster]

2011

  1. Atsushi Fujita, Hiroshi Itsuki, and Hitoshi Matsubara. Detecting Real Money Traders in MMORPG by Using Trading Network. In Proceedings of the 7th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), pp. 26-31, Oct., 2011. [Paper] [Slides]
  2. Tomoko Izumi, Kenji Imamura, Genichiro Kikui, Atsushi Fujita, and Satoshi Sato. Paraphrasing Japanese Light Verb Constructions: Towards the Normalization of Complex Predicates. International Journal of Computer Processing of Languages, Vol. 23, No. 2, pp. 147-167, 2011. (DOI)
  3. Atsushi Fujita, Katsuhiro Ikushima, Satoshi Sato. Automatic Generation of Listing Ads and Assessment of Their Performance on Attracting Customers: A Case Study on Restaurant Domain. Journal of Information Processing Society of Japan, Vol. 52, No. 6, pp. 2031-2044, Jun., 2011. (in Japanese) [Paper]

2010

  1. Hiroshi Itsuki, Asuka Takeuchi, Atsushi Fujita, Hitoshi Matsubara. Supporting MMORPG Operators in Dealing with Real-Money Trading. Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol. 22, No. 6, pp. 757-761, Dec., 2010. (in Japanese)
  2. Atsushi Fujita. Typology of Paraphrases and Approaches to Compute Them. Workshop on Corpus-Based Approaches to Paraphrasing and Nominalization, Dec., 2010. (Invited talk) [Slides]
  3. Hiroshi Itsuki, Asuka Takeuchi, Atsushi Fujita, and Hitoshi Matsubara. Exploiting MMORPG Log Data toward Efficient RMT Player Detection. In Proceedings of the 7th International Conference on Advances in Computer Entertainment Technology (ACE), pp. 118-119, Nov., 2010. [Paper] [Poster]
  4. Masahiro Kojima, Masaki Murata, Jun'ichi Kazama, Kow Kuroda, Atsushi Fujita, Eiji Aramaki, Masaaki Tsuchida, Yasuhiko Watanabe, and Kentaro Torisawa. Using Various Features in Machine Learning to Obtain High Levels of Performance for Recognition of Japanese Notational Variants. In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation (PACLIC), pp. 653-660, Nov., 2010. (Paper)
  5. Koichi Takeuchi, Kentaro Inui, Nao Takeuchi, and Atsushi Fujita. A Thesaurus of Predicate-Argument Structure for Japanese Verbs to Deal with Granularity of Verb Meanings. In Proceedings of the 8th Workshop on Asian Language Resources (ALR), pp. 1-8, Aug., 2010. (Paper)
  6. Atsushi Fujita, Katsuhiro Ikushima, Satoshi Sato, Ryo Kamite, Ko Ishiyama, and Osamu Tamachi. Automatic Generation of Listing Ads by Reusing Promotional Texts. In Proceedings of the 12th International Conference on Electronic Commerce (ICEC), pp. 191-200, Aug., 2010. [Paper] [Slides]
  7. Tomoko Izumi, Kenji Imamura, Genichiro Kikui, Atsushi Fujita, and Satoshi Sato. Paraphrasing Japanese Light Verb Constructions: Towards the Normalization of Complex Predicates. In Proceedings of the 23rd International Conference on the Computer Processing of Oriental Languages (ICCPOL), pp. 55-62, Jul., 2010.
  8. Atsushi Fujita and Satoshi Sato. Measuring the Appropriateness of Automatically Generated Phrasal Paraphrases. Journal of Natural Language Processing, Vol. 17, No. 1, pp. 183-219, Jan., 2010. [Paper] (DOI)

2009

  1. Atsushi Fujita. Paraphrase Generation. In Encyclopedia of Natural Language Processing, Section 2.8.1, pp. 220-223, Kyoritsu Shuppan Co., Ltd., Dec., 2009. (in Japanese) (Publisher) (Amazon.co.jp) (Digital version @ Amazon.co.jp)
  2. Atsushi Fujita. Surface Generation. In Encyclopedia of Natural Language Processing, Section 2.7.2, pp. 216-217, Kyoritsu Shuppan Co., Ltd., Dec., 2009. (in Japanese) (Publisher) (Amazon.co.jp) (Digital version @ Amazon.co.jp)

2008

  1. Atsushi Fujita and Satoshi Sato. Toward Automatic Compilation of Phrasal Thesaurus. NSF Sponsored Symposium on Semantic Knowledge Discovery, Organization and Use, Nov., 2008. [Paper] [Poster]
  2. Atsushi Fujita and Satoshi Sato. A Probabilistic Model for Measuring Grammaticality and Similarity of Automatically Generated Paraphrases of Predicate Phrases. In Proceedings of the 22nd International Conference on Computational Linguistics (COLING), pp. 225-232, Aug., 2008. [Paper] [Slides]
  3. Atsushi Fujita and Satoshi Sato. Computing Paraphrasability of Syntactic Variants Using Web Snippets. In Proceedings of the 3rd International Joint Conference on Natural Language Processing (IJCNLP), pp. 537-544, Jan., 2008. [Paper] [Slides]

2007

  1. Atsushi Fujita and Satoshi Sato. Computing Paraphrasability between Syntactic Variants of Predicate Phrases. In Information Processing Society of Japan SIG Notes, NL-182-4, pp. 23-30, Nov., 2007. [Paper]
  2. Atsushi Fujita, Shuhei Kato, Naoki Kato, and Satoshi Sato. A Compositional Approach toward Dynamic Phrasal Thesaurus. In Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing (WTEP), pp. 151-158, Jun., 2007. [Paper] [Slides]

2006

  1. Atsushi Fujita. Issues and Applications of Automatic Paraphrase Generation. In Proceedings of the 2006 Tokai-section Joint Convention of Institutes of Electrical Engineering, Symposium on Natural Language Processsing and its Application, S2-5, 2 pages, Sep., 2006. (Invited talk) (in Japanese) [Paper] [Slides]
  2. Atsushi Fujita, Naruaki Masuno, Satoshi Sato, and Takehito Utsuro. Adjective-to-Verb Paraphrasing in Japanese Based on Lexical Constraints of Verbs. In Proceedings of the 4th International Natural Language Generation Conference (INLG), pp. 41-43, Jul., 2006. [Paper] [Slides]
  3. Atsushi Fujita and Kentaro Inui. Building a Paraphrase Corpus Based on Class-oriented Candidate Generation. Journal of Natural Language Processing, Vol. 13, No. 3, pp. 133-150, Jul., 2006. (in Japanese) [Paper] (DOI)
  4. Toru Hirano, Ryu Iida, Atsushi Fujita, Kentaro Inui, and Yuji Matsumoto. Augmenting a Semantic Verb Lexicon with a Large Scale Collection of Example Sentences. Journal of Natural Language Processing, Vol. 13, No. 3, pp. 113-132, Jul., 2006. (in Japanese) (DOI)
  5. Atsushi Fujita, Kentaro Furihata, Kentaro Inui, and Yuji Matsumoto. Paraphrase Generation Based on Lexical Conceptual Structure: A Case Study on Paraphrasing of Light-verb Constructions. Journal of Information Processing Society of Japan, Vol. 47, No. 6, pp. 1963-1975, Jun., 2006. (in Japanese) [Paper]
  6. Koichi Takeuchi, Kentaro Inui, and Atsushi Fujita. Construction of Compositional Lexical Database Based on Lexical Conceptual Structure for Japanese Verbs. In Lexicon Forum, No. 2, pp. 85-120, Hitsuji Shobo, Jun., 2006. (in Japanese) (Amazon.co.jp)
  7. Kentaro Inui and Atsushi Fujita. A Lexical Semantics-Based Approach to Computational Modeling of Lexico-Syntactic Paraphrasing. In Lexicon Forum, No. 2, pp. 27-55, Hitsuji Shobo, Jun., 2006. (in Japanese) [Paper (draft)] (Amazon.co.jp)
  8. Kentaro Inui, Toru Hirano, Ryu Iida, Atsushi Fujita, and Yuji Matsumoto. Augmenting a Semantic Verb Lexicon with a Large Scale Collection of Example Sentences. In Proceedings of the 5th International Conference on Language Resources and Evaluation (LREC), pp. 365-368, May, 2006. (Paper)

2005

  1. Atsushi Fujita and Kentaro Inui. A Class-oriented Approach to Building a Paraphrase Corpus. In Proceedings of the 3rd International Workshop on Paraphrasing (IWP), pp. 25-32, Oct., 2005. [Paper] [Slides]
  2. Atsushi Fujita, Kentaro Inui, and Yuji Matsumoto. Exploiting Lexical Conceptual Structure for Paraphrase Generation. In Proceedings of the 2nd International Joint Conference on Natural Language Processing (IJCNLP), Lecture Notes in Artificial Intelligence, Vol. 3651, pp. 908-919, Springer-Verlag, Oct., 2005. [Paper (draft)] [Slides] (Publisher) (Amazon.co.jp)
  3. Atsushi Fujita, Kentaro Inui, and Yuji Matsumoto. Detection of Incorrect Case Assignments in Paraphrase Generation. In Lecture Notes in Artificial Intelligence, Vol. 3248, pp. 555-565, Springer-Verlag, Mar., 2005. [Paper (draft)] (Publisher) (Amazon.co.jp)

2004

  1. Kentaro Inui and Atsushi Fujita. A Survey on Paraphrase Generation and Recognition. Journal of Natural Language Processing, Vol. 11, No. 5, pp. 151-198, Oct., 2004. (Invited paper) (in Japanese) [Paper] (DOI)
  2. Atsushi Fujita, Kentaro Furihata, Kentaro Inui, Yuji Matsumoto, and Koichi Takeuchi. Paraphrasing of Japanese Light-verb Constructions Based on Lexical Conceptual Structure. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL) Workshop on Multiword Expressions: Integrating Processing, pp. 9-16, Jul., 2004. [Paper]
  3. Atsushi Fujita, Kentaro Inui, and Yuji Matsumoto. Detection of Incorrect Case Assignments in Automatically Generated Paraphrases. Journal of Information Processing Society of Japan, Vol. 45, No. 4, pp. 1176-1187, Apr., 2004. (in Japanese) [Paper]
  4. Atsushi Fujita, Kentaro Inui, and Yuji Matsumoto. Detection of Incorrect Case Assignments in Automatically Generated Paraphrases of Japanese Sentences. In Proceedings of the 1st International Joint Conference on Natural Language Processing (IJCNLP), pp. 14-21, Mar., 2004. (Best paper award nominee) [Paper]

2003

  1. Atsushi Fujita and Kentaro Inui. Exploring Transfer Errors in Lexical and Structural Paraphrasing. Journal of Information Processing Society of Japan, Vol. 44, No. 11, pp. 2826-2838, Nov., 2003. (in Japanese) [Paper]
  2. Kentaro Inui, Atsushi Fujita, Tetsuro Takahashi, Ryu Iida, and Tomoya Iwakura. Text Simplification for Reading Assistance: A Project Note. In Proceedings of the 2nd International Workshop on Paraphrasing: Paraphrase Acquisition and Applications (IWP), pp. 9-16, Jul., 2003. (Paper)

2001

  1. Tetsuro Takahashi, Tomoya Iwakura, Ryu Iida, Atsushi Fujita, and Kentaro Inui. KURA: A Transfer-based Lexico-structural Paraphrasing Engine. In Proceedings of the 6th Natural Language Processing Pacific Rim Symposium (NLPRS) Workshop on Automatic Paraphrasing: Theories and Applications, pp. 37-46, Nov., 2001. [Paper]

Other designated presentations

Thesis

Doctoral dissertation
Atsushi Fujita. Automatic Generation of Syntactically Well-formed and Semantically Appropriate Paraphrases. Graduate School of Information Science, Nara Institute of Science and Technology (NAIST), Mar., 2005. [Thesis (latest)] (Conferment) (2007.12.17: some small mistakes were corrected.)