no code implementations • WAT 2022 • Toshiaki Nakazawa, Hideya Mino, Isao Goto, Raj Dabre, Shohei Higashiyama, Shantipriya Parida, Anoop Kunchukuttan, Makoto Morishita, Ondřej Bojar, Chenhui Chu, Akiko Eriguchi, Kaori Abe, Yusuke Oda, Sadao Kurohashi
This paper presents the results of the shared tasks from the 9th workshop on Asian translation (WAT2022).
no code implementations • dialdoc (ACL) 2022 • Takashi Kodama, Ribeka Tanaka, Sadao Kurohashi
We work on a recommendation dialogue system to help a user understand the appealing points of some target (e. g., a movie).
no code implementations • Findings (EMNLP) 2021 • Masato Umakoshi, Yugo Murawaki, Sadao Kurohashi
Parallel texts of Japanese and a non-pro-drop language have the potential of improving the performance of Japanese zero anaphora resolution (ZAR) because pronouns dropped in the former are usually mentioned explicitly in the latter.
no code implementations • ACL (WAT) 2021 • Toshiaki Nakazawa, Hideki Nakayama, Chenchen Ding, Raj Dabre, Shohei Higashiyama, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Shantipriya Parida, Ondřej Bojar, Chenhui Chu, Akiko Eriguchi, Kaori Abe, Yusuke Oda, Sadao Kurohashi
This paper presents the results of the shared tasks from the 8th workshop on Asian translation (WAT2021).
1 code implementation • ACL 2022 • Yongmin Kim, Chenhui Chu, Sadao Kurohashi
Existing visual grounding datasets are artificially made, where every query regarding an entity must be able to be grounded to a corresponding image region, i. e., answerable.
1 code implementation • COLING (CRAC) 2022 • Nobuhiro Ueda, Sadao Kurohashi
Bridging reference resolution is the task of finding nouns that complement essential information of another noun.
no code implementations • NAACL (ACL) 2022 • Prakhar Saxena, Yin Jou Huang, Sadao Kurohashi
Each person has a unique personality which affects how they feel and convey emotions.
Ranked #25 on
Emotion Recognition in Conversation
on MELD
no code implementations • EMNLP 2020 • Kazumasa Omura, Daisuke Kawahara, Sadao Kurohashi
We present a scalable, low-bias, and low-cost method for building a commonsense inference dataset that combines automatic extraction from a corpus and crowdsourcing.
no code implementations • IWSLT 2017 • Raj Dabre, Fabien Cromieres, Sadao Kurohashi
We describe here our Machine Translation (MT) model and the results we obtained for the IWSLT 2017 Multilingual Shared Task.
no code implementations • CLIB 2022 • Iglika Nikolova-Stoupak, Shuichiro Shimizu, Chenhui Chu, Sadao Kurohashi
The corpus utilised to train machine translation models in the study is CCMatrix, provided by OPUS.
no code implementations • NAACL (ACL) 2022 • Takumi Yoshikoshi, Hayato Atarashi, Takashi Kodama, Sadao Kurohashi
In this study, we propose a dialogue system that responds appropriately following the topic by selecting the entity with the highest “topicality.” In topicality estimation, the model is trained through self-supervised learning that regards entities that appear in both context and response as the topic entities.
no code implementations • COLING 2022 • Kazumasa Omura, Sadao Kurohashi
Contingent reasoning is one of the essential abilities in natural language understanding, and many language resources annotated with contingent relations have been constructed.
no code implementations • AACL (WAT) 2020 • Zhuoyuan Mao, Yibin Shen, Chenhui Chu, Sadao Kurohashi, Cheqing Jin
This paper describes the Japanese-Chinese Neural Machine Translation (NMT) system submitted by the joint team of Kyoto University and East China Normal University (Kyoto-U+ECNU) to WAT 2020 (Nakazawa et al., 2020).
no code implementations • AACL (WAT) 2020 • Toshiaki Nakazawa, Hideki Nakayama, Chenchen Ding, Raj Dabre, Shohei Higashiyama, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Shantipriya Parida, Ondřej Bojar, Sadao Kurohashi
This paper presents the results of the shared tasks from the 7th workshop on Asian translation (WAT2020).
1 code implementation • LREC 2022 • Felix Virgo, Fei Cheng, Sadao Kurohashi
However, the amount of training data for tasks like duration question answering, i. e., McTACO, is very limited, suggesting a need for external duration information to improve this task.
1 code implementation • LREC 2022 • Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, Sadao Kurohashi
In this paper, we first propose a novel relation annotation schema for investigating the medical and temporal relations between medical entities in Japanese medical reports.
no code implementations • LREC 2022 • Taro Okahisa, Ribeka Tanaka, Takashi Kodama, Yin Jou Huang, Sadao Kurohashi
Interview is an efficient way to elicit knowledge from experts of different domains.
no code implementations • 3 Mar 2025 • Sakiko Yahata, Zhen Wan, Fei Cheng, Sadao Kurohashi, Hisahiko Sato, Ryozo Nagai
Thus, we propose a novel task, Causal Tree Extraction (CTE), which receives a case report and generates a causal tree with the primary disease as the root, providing an intuitive understanding of a case's diagnostic process.
no code implementations • 25 Feb 2025 • Qianying Liu, Katrina Qiyao Wang, Fei Cheng, Sadao Kurohashi
Large Language Models have garnered significant attention for their capabilities in multilingual natural language processing, while studies on risks associated with cross biases are limited to immediate context preferences.
no code implementations • 20 Aug 2024 • Chengzhi Zhong, Fei Cheng, Qianying Liu, Junfeng Jiang, Zhen Wan, Chenhui Chu, Yugo Murawaki, Sadao Kurohashi
We examine the latent language of three typical categories of models for Japanese processing: Llama2, an English-centric model; Swallow, an English-centric model with continued pre-training in Japanese; and LLM-jp, a model pre-trained on balanced English and Japanese corpora.
no code implementations • 4 Jul 2024 • LLM-jp, :, Akiko Aizawa, Eiji Aramaki, Bowen Chen, Fei Cheng, Hiroyuki Deguchi, Rintaro Enomoto, Kazuki Fujii, Kensuke Fukumoto, Takuya Fukushima, Namgi Han, Yuto Harada, Chikara Hashimoto, Tatsuya Hiraoka, Shohei Hisada, Sosuke Hosokawa, Lu Jie, Keisuke Kamata, Teruhito Kanazawa, Hiroki Kanezashi, Hiroshi Kataoka, Satoru Katsumata, Daisuke Kawahara, Seiya Kawano, Atsushi Keyaki, Keisuke Kiryu, Hirokazu Kiyomaru, Takashi Kodama, Takahiro Kubo, Yohei Kuga, Ryoma Kumon, Shuhei Kurita, Sadao Kurohashi, Conglong Li, Taiki Maekawa, Hiroshi Matsuda, Yusuke Miyao, Kentaro Mizuki, Sakae Mizuki, Yugo Murawaki, Akim Mousterou, Ryo Nakamura, Taishi Nakamura, Kouta Nakayama, Tomoka Nakazato, Takuro Niitsuma, Jiro Nishitoba, Yusuke Oda, Hayato Ogawa, Takumi Okamoto, Naoaki Okazaki, Yohei Oseki, Shintaro Ozaki, Koki Ryu, Rafal Rzepka, Keisuke Sakaguchi, Shota Sasaki, Satoshi Sekine, Kohei Suda, Saku Sugawara, Issa Sugiura, Hiroaki Sugiyama, Hisami Suzuki, Jun Suzuki, Toyotaro Suzumura, Kensuke Tachibana, Yu Takagi, Kyosuke Takami, Koichi Takeda, Masashi Takeshita, Masahiro Tanaka, Kenjiro Taura, Arseny Tolmachev, Nobuhiro Ueda, Zhen Wan, Shuntaro Yada, Sakiko Yahata, Yuya Yamamoto, Yusuke Yamauchi, Hitomi Yanaka, Rio Yokota, Koichiro Yoshino
This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs).
no code implementations • 21 May 2024 • Sirou Chen, Sakiko Yahata, Shuichiro Shimizu, Zhengdong Yang, Yihang Li, Chenhui Chu, Sadao Kurohashi
Emotion plays a crucial role in human conversation.
2 code implementations • 28 Mar 2024 • Nobuhiro Ueda, Hideko Habe, Yoko Matsui, Akishige Yuguchi, Seiya Kawano, Yasutomo Kawanishi, Sadao Kurohashi, Koichiro Yoshino
Understanding expressions that refer to the physical world is crucial for such human-assisting systems in the real world, as robots that must perform actions that are expected by users.
no code implementations • 27 Mar 2024 • Felix Virgo, Fei Cheng, Lis Kanashiro Pereira, Masayuki Asahara, Ichiro Kobayashi, Sadao Kurohashi
We propose a voting-driven semi-supervised approach to automatically acquire the typical duration of an event and use it as pseudo-labeled data.
2 code implementations • 6 Mar 2024 • Yikun Sun, Zhen Wan, Nobuhiro Ueda, Sakiko Yahata, Fei Cheng, Chenhui Chu, Sadao Kurohashi
The creation of instruction data and evaluation benchmarks for serving Large language models often involves enormous human annotation.
no code implementations • 21 Feb 2024 • Takashi Kodama, Hirokazu Kiyomaru, Yin Jou Huang, Sadao Kurohashi
Since there are no existing annotated resources for the analysis, we constructed RecMind, a Japanese movie recommendation dialogue dataset with annotations of the seeker's internal state at the entity level.
1 code implementation • 7 Nov 2023 • Haiyue Song, Raj Dabre, Chenhui Chu, Atsushi Fujita, Sadao Kurohashi
To create the parallel corpora, we propose a dynamic programming based sentence alignment algorithm which leverages the cosine similarity of machine-translated sentences.
1 code implementation • 31 Oct 2023 • Yihang Li, Shuichiro Shimizu, Chenhui Chu, Sadao Kurohashi, Wei Li
In addition to the extensive training set, EVA contains a video-helpful evaluation set in which subtitles are ambiguous, and videos are guaranteed helpful for disambiguation.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Fei Cheng, Masayuki Asahara, Ichiro Kobayashi, Sadao Kurohashi
Temporal relation classification is a pair-wise task for identifying the relation of a temporal link (TLINK) between two mentions, i. e. event, time, and document creation time (DCT).
1 code implementation • 5 Oct 2023 • Zhen Wan, Yating Zhang, Yexiang Wang, Fei Cheng, Sadao Kurohashi
In the zero-shot setting of four Chinese legal tasks, our method improves accuracy by 33. 3\% compared to the direct generation by GPT-4.
no code implementations • 31 Jul 2023 • Haiyue Song, Raj Dabre, Chenhui Chu, Sadao Kurohashi, Eiichiro Sumita
Sub-word segmentation is an essential pre-processing step for Neural Machine Translation (NMT).
1 code implementation • 26 May 2023 • Tatsuro Inaba, Hirokazu Kiyomaru, Fei Cheng, Sadao Kurohashi
Large language models (LLMs) have achieved impressive performance on various reasoning tasks.
no code implementations • 17 May 2023 • Zhuoyuan Mao, Haiyue Song, Raj Dabre, Chenhui Chu, Sadao Kurohashi
The language-independency of encoded representations within multilingual neural machine translation (MNMT) models is crucial for their generalization ability on zero-shot translation.
no code implementations • 16 May 2023 • Zhuoyuan Mao, Raj Dabre, Qianying Liu, Haiyue Song, Chenhui Chu, Sadao Kurohashi
This paper studies the impact of layer normalization (LayerNorm) on zero-shot translation (ZST).
1 code implementation • 16 May 2023 • Shuichiro Shimizu, Chenhui Chu, Sheng Li, Sadao Kurohashi
We present a new task, speech dialogue translation mediating speakers of different languages.
1 code implementation • 15 May 2023 • Junfeng Jiang, Chengzhang Dong, Sadao Kurohashi, Akiko Aizawa
In this paper, we provide a feasible definition of dialogue segmentation points with the help of document-grounded dialogues and release a large-scale supervised dataset called SuperDialseg, containing 9, 478 dialogues based on two prevalent document-grounded dialogue corpora, and also inherit their useful dialogue-related annotations.
no code implementations • 12 May 2023 • Qianying Liu, Dongsheng Yang, Wenjie Zhong, Fei Cheng, Sadao Kurohashi
Numerical reasoning over table-and-text hybrid passages, such as financial reports, poses significant challenges and has numerous potential applications.
1 code implementation • 3 May 2023 • Zhen Wan, Fei Cheng, Zhuoyuan Mao, Qianying Liu, Haiyue Song, Jiwei Li, Sadao Kurohashi
In spite of the potential for ground-breaking achievements offered by large language models (LLMs) (e. g., GPT-3), they still lag significantly behind fully-supervised baselines (e. g., fine-tuned BERT) in relation extraction (RE).
1 code implementation • 29 Nov 2022 • Yibin Shen, Qianying Liu, Zhuoyuan Mao, Fei Cheng, Sadao Kurohashi
Solving math word problems is the task that analyses the relation of quantities and requires an accurate understanding of contextual natural language information.
1 code implementation • 21 Oct 2022 • Zhen Wan, Qianying Liu, Zhuoyuan Mao, Fei Cheng, Sadao Kurohashi, Jiwei Li
Relation extraction (RE) has achieved remarkable progress with the help of pre-trained language models.
no code implementations • 13 Oct 2022 • Qianying Liu, Wenyu Guan, Jianhao Shen, Fei Cheng, Sadao Kurohashi
To address this problem, we propose a novel search algorithm with combinatorial strategy \textbf{ComSearch}, which can compress the search space by excluding mathematically equivalent equations.
1 code implementation • 21 Sep 2022 • Yibin Shen, Qianying Liu, Zhuoyuan Mao, Zhen Wan, Fei Cheng, Sadao Kurohashi
To solve Math Word Problems, human students leverage diverse reasoning logic that reaches different possible equation solutions.
1 code implementation • 31 May 2022 • Zhuoyuan Mao, Chenhui Chu, Sadao Kurohashi
Massively multilingual sentence representation models, e. g., LASER, SBERT-distill, and LaBSE, help significantly improve cross-lingual downstream tasks.
no code implementations • 18 May 2022 • Zhen Wan, Fei Cheng, Qianying Liu, Zhuoyuan Mao, Haiyue Song, Sadao Kurohashi
Contrastive pre-training on distant supervision has shown remarkable effectiveness in improving supervised relation extraction tasks.
no code implementations • Findings (NAACL) 2022 • Zhuoyuan Mao, Chenhui Chu, Raj Dabre, Haiyue Song, Zhen Wan, Sadao Kurohashi
Meanwhile, the contrastive objective can implicitly utilize automatically learned word alignment, which has not been explored in many-to-many NMT.
1 code implementation • 8 Apr 2022 • Qianying Liu, Zhuo Gong, Zhengdong Yang, Yuhang Yang, Sheng Li, Chenchen Ding, Nobuaki Minematsu, Hao Huang, Fei Cheng, Chenhui Chu, Sadao Kurohashi
Low-resource speech recognition has been long-suffering from insufficient training data.
1 code implementation • 20 Jan 2022 • Zhuoyuan Mao, Chenhui Chu, Sadao Kurohashi
In the present study, we propose novel sequence-to-sequence pre-training objectives for low-resource machine translation (NMT): Japanese-specific sequence to sequence (JASS) for language pairs involving Japanese as the source or target language, and English-specific sequence to sequence (ENSS) for language pairs involving English.
Low Resource Neural Machine Translation
Low-Resource Neural Machine Translation
+2
1 code implementation • LREC 2022 • Yihang Li, Shuichiro Shimizu, Weiqi Gu, Chenhui Chu, Sadao Kurohashi
Existing multimodal machine translation (MMT) datasets consist of images and video captions or general subtitles, which rarely contain linguistic ambiguity, making visual information not so effective to generate appropriate translations.
no code implementations • 10 Nov 2021 • Qianying Liu, Fei Cheng, Sadao Kurohashi
Meta learning with auxiliary languages has demonstrated promising improvements for cross-lingual natural language processing.
1 code implementation • 8 Nov 2021 • Fei Cheng, Shuntaro Yada, Ribeka Tanaka, Eiji Aramaki, Sadao Kurohashi
We present an open-access natural language processing toolkit for Japanese medical information extraction.
no code implementations • ACL 2021 • Weiqi Gu, Haiyue Song, Chenhui Chu, Sadao Kurohashi
Video-guided machine translation, as one type of multimodal machine translations, aims to engage video contents as auxiliary information to address the word sense ambiguity problem in machine translation.
no code implementations • NAACL 2021 • Hirokazu Kiyomaru, Sadao Kurohashi
The model is trained to maximize the similarity between the representation of the target sentence with its context and that of the masked target sentence with the same context.
1 code implementation • ACL 2021 • Zhuoyuan Mao, Prakhar Gupta, Pei Wang, Chenhui Chu, Martin Jaggi, Sadao Kurohashi
Large-scale models for learning fixed-dimensional cross-lingual sentence representations like LASER (Artetxe and Schwenk, 2019b) lead to significant improvement in performance on downstream tasks.
1 code implementation • NAACL 2021 • Honai Ueoka, Yugo Murawaki, Sadao Kurohashi
With advances in neural language models, the focus of linguistic steganography has shifted from edit-based approaches to generation-based ones.
no code implementations • EACL 2021 • Yin Jou Huang, Sadao Kurohashi
In this paper, we propose a heterogeneous graph based model for extractive summarization that incorporates both discourse and coreference relations.
no code implementations • 5 Dec 2020 • Takashi Kodama, Ribeka Tanaka, Sadao Kurohashi
In this paper, we model the UIS in dialogues, taking movie recommendation dialogues as examples, and construct a dialogue system that changes its response based on the UIS.
1 code implementation • COLING 2020 • Nobuhiro Ueda, Daisuke Kawahara, Sadao Kurohashi
The meaning of natural language text is supported by cohesion among various kinds of entities, including coreference relations, predicate-argument structures, and bridging anaphora relations.
no code implementations • COLING 2020 • Oleksandr Harust, Yugo Murawaki, Sadao Kurohashi
We propose a novel task of native-like expression identification by contrasting texts written by native speakers and those by proficient second language speakers.
1 code implementation • 4 Oct 2020 • Qianying Liu, Wenyu Guan, Sujian Li, Fei Cheng, Daisuke Kawahara, Sadao Kurohashi
Automatically solving math word problems is a critical task in the field of natural language processing.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng, Fei Cheng, Daisuke Kawahara, Sadao Kurohashi
We propose a novel Sequence-to-Unordered-Multi-Tree (Seq2UMTree) model to minimize the effects of exposure bias by limiting the decoding length to three within a triplet and removing the order among triplets.
no code implementations • EMNLP (NLP-COVID19) 2020 • Akiko Aizawa, Frederic Bergeron, Junjie Chen, Fei Cheng, Katsuhiko Hayashi, Kentaro Inui, Hiroyoshi Ito, Daisuke Kawahara, Masaru Kitsuregawa, Hirokazu Kiyomaru, Masaki Kobayashi, Takashi Kodama, Sadao Kurohashi, Qianying Liu, Masaki Matsubara, Yusuke Miyao, Atsuyuki Morishima, Yugo Murawaki, Kazumasa Omura, Haiyue Song, Eiichiro Sumita, Shinji Suzuki, Ribeka Tanaka, Yu Tanaka, Masashi Toyoda, Nobuhiro Ueda, Honai Ueoka, Masao Utiyama, Ying Zhong
The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education.
no code implementations • ACL 2020 • Haiyue Song, Raj Dabre, Zhuoyuan Mao, Fei Cheng, Sadao Kurohashi, Eiichiro Sumita
Sequence-to-sequence (S2S) pre-training using large monolingual data is known to improve performance for various S2S NLP tasks.
no code implementations • ACL 2020 • Yu Tanaka, Yugo Murawaki, Daisuke Kawahara, Sadao Kurohashi
User generated texts contain many typos for which correction is necessary for NLP systems to work.
1 code implementation • LREC 2020 • Zhuoyuan Mao, Fabien Cromieres, Raj Dabre, Haiyue Song, Sadao Kurohashi
Monolingual pre-training approaches such as MASS (MAsked Sequence to Sequence) are extremely effective in boosting NMT quality for languages with small parallel corpora.
no code implementations • LREC 2020 • Shuntaro Yada, Ayami Joh, Ribeka Tanaka, Fei Cheng, Eiji Aramaki, Sadao Kurohashi
Applying natural language processing (NLP) to medical and clinical texts can bring important social benefits by mining valuable information from unstructured text.
no code implementations • LREC 2020 • Yudai Kishimoto, Yugo Murawaki, Sadao Kurohashi
BERT, a neural network-based language model pre-trained on large corpora, is a breakthrough in natural language processing, significantly outperforming previous state-of-the-art models in numerous tasks.
General Classification
Implicit Discourse Relation Classification
+4
no code implementations • LREC 2020 • Ritsuko Iwai, Daisuke Kawahara, Takatsune Kumada, Sadao Kurohashi
In this study, we collect personality words, using word embeddings, and construct a personality dictionary with weights for Big Five traits.
no code implementations • LREC 2020 • Ritsuko Iwai, Daisuke Kawahara, Takatsune Kumada, Sadao Kurohashi
Using them, we automatically extracted collocations between personality descriptors and driving-related behavior from a driving behavior and subjectivity corpus (1, 803, 328 sentences after filtering) and obtained unique 5, 334 collocations.
no code implementations • 23 Jan 2020 • Haiyue Song, Raj Dabre, Zhuoyuan Mao, Fei Cheng, Sadao Kurohashi, Eiichiro Sumita
To this end, we propose to exploit monolingual corpora of other languages to complement the scarcity of monolingual corpora for the LOI.
1 code implementation • LREC 2020 • Haiyue Song, Raj Dabre, Atsushi Fujita, Sadao Kurohashi
To address this, we examine a language independent framework for parallel corpus mining which is a quick and effective way to mine a parallel corpus from publicly available lectures at Coursera.
no code implementations • 28 Nov 2019 • Abhishek Kumar, Asif Ekbal, Daisuke Kawahra, Sadao Kurohashi
Our network also boosts the performance of emotion analysis by 5 F-score points on Stance Sentiment Emotion Corpus.
1 code implementation • 21 Nov 2019 • Reid Pryzant, Richard Diehl Martinez, Nathan Dass, Sadao Kurohashi, Dan Jurafsky, Diyi Yang
To address this issue, we introduce a novel testbed for natural language generation: automatically bringing inappropriately subjective text into a neutral point of view ("neutralizing" biased text).
no code implementations • WS 2019 • Norio Takahashi, Tomohide Shibata, Daisuke Kawahara, Sadao Kurohashi
To improve the accuracy of predicate-argument structure (PAS) analysis, large-scale training data and knowledge for PAS analysis are indispensable.
no code implementations • WS 2019 • Toshiaki Nakazawa, Nobushige Doi, Shohei Higashiyama, Chenchen Ding, Raj Dabre, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Yusuke Oda, Shantipriya Parida, Ond{\v{r}}ej Bojar, Sadao Kurohashi
This paper presents the results of the shared tasks from the 6th workshop on Asian translation (WAT2019) including Ja↔En, Ja↔Zh scientific paper translation subtasks, Ja↔En, Ja↔Ko, Ja↔En patent translation subtasks, Hi↔En, My↔En, Km↔En, Ta↔En mixed domain subtasks and Ru↔Ja news commentary translation task.
no code implementations • WS 2019 • Hirokazu Kiyomaru, Kazumasa Omura, Yugo Murawaki, Daisuke Kawahara, Sadao Kurohashi
Typical event sequences are an important class of commonsense knowledge.
no code implementations • IJCNLP 2019 • Jun Saito, Yugo Murawaki, Sadao Kurohashi
Recognizing affective events that trigger positive or negative sentiment has a wide range of natural language processing applications but remains a challenging problem mainly because the polarity of an event is not necessarily predictable from its constituent words.
no code implementations • WS 2019 • Fabien Cromieres, Sadao Kurohashi
We describe here the experiments we did for the the news translation shared task of WMT 2019.
no code implementations • NAACL 2019 • Yin Jou Huang, Jing Lu, Sadao Kurohashi, Vincent Ng
Argument compatibility is a linguistic condition that is frequently incorporated into modern event coreference resolution systems.
no code implementations • NAACL 2019 • Arseny Tolmachev, Daisuke Kawahara, Sadao Kurohashi
Morphological analyzers are trained on data hand-annotated with segmentation boundaries and part of speech tags.
1 code implementation • 8 May 2019 • Wataru Sakata, Tomohide Shibata, Ribeka Tanaka, Sadao Kurohashi
On the other hand, the relevance between the query and answer can be learned by using QA pairs in a FAQ database.
1 code implementation • EMNLP 2018 • Arseny Tolmachev, Daisuke Kawahara, Sadao Kurohashi
We present a three-part toolkit for developing morphological analyzers for languages without natural word boundaries.
no code implementations • 3 Aug 2018 • Md. Shad Akhtar, Deepanway Ghosal, Asif Ekbal, Pushpak Bhattacharyya, Sadao Kurohashi
In this paper, through multi-task ensemble framework we address three problems of emotion and sentiment analysis i. e. "emotion classification & intensity", "valence, arousal & dominance for emotion" and "valence & arousal} for sentiment".
no code implementations • COLING 2018 • Yudai Kishimoto, Yugo Murawaki, Sadao Kurohashi
Identifying discourse relations that are not overtly marked with discourse connectives remains a challenging problem.
General Classification
Implicit Discourse Relation Classification
+4
1 code implementation • COLING 2018 • Naoki Otani, Hirokazu Kiyomaru, Daisuke Kawahara, Sadao Kurohashi
Considerable effort has been devoted to building commonsense knowledge bases.
no code implementations • ACL 2018 • Tomohide Shibata, Sadao Kurohashi
Our experimental results demonstrate the proposed method can improve the performance of the inter-sentential zero anaphora resolution drastically, which is a notoriously difficult task in predicate argument structure analysis.
no code implementations • ACL 2018 • Shuhei Kurita, Daisuke Kawahara, Sadao Kurohashi
Japanese predicate-argument structure (PAS) analysis involves zero anaphora resolution, which is notoriously difficult.
no code implementations • NAACL 2018 • Abhishek Kumar, Daisuke Kawahara, Sadao Kurohashi
We propose a novel two-layered attention network based on Bidirectional Long Short-Term Memory for sentiment analysis.
no code implementations • WS 2017 • Toshiaki Nakazawa, Shohei Higashiyama, Chenchen Ding, Hideya Mino, Isao Goto, Hideto Kazawa, Yusuke Oda, Graham Neubig, Sadao Kurohashi
For the WAT2017, 12 institutions participated in the shared tasks.
1 code implementation • WS 2017 • Fabien Cromieres, Raj Dabre, Toshiaki Nakazawa, Sadao Kurohashi
We describe here our approaches and results on the WAT 2017 shared translation tasks.
2 code implementations • 3 Oct 2017 • Raj Dabre, Sadao Kurohashi
Multilinguality is gradually becoming ubiquitous in the sense that more and more researchers have successfully shown that using additional languages help improve the results in many Natural Language Processing tasks.
no code implementations • WS 2017 • Daisuke Kawahara, Yuta Hayashibe, Hajime Morita, Sadao Kurohashi
This paper presents a joint model for morphological and dependency analysis based on automatically acquired lexical knowledge.
no code implementations • WS 2017 • Arseny Tolmachev, Sadao Kurohashi
Flashcard systems are effective tools for learning words but have their limitations in teaching word usage.
no code implementations • WS 2017 • Yin Jou Huang, Sadao Kurohashi
Shared arguments of event knowledge encode patterns of role shifting in successive events.
no code implementations • ACL 2017 • Shuhei Kurita, Daisuke Kawahara, Sadao Kurohashi
We present neural network-based joint models for Chinese word segmentation, POS tagging and dependency parsing.
no code implementations • ACL 2017 • Chenhui Chu, Raj Dabre, Sadao Kurohashi
In this paper, we propose a novel domain adaptation method named {``}mixed fine tuning{''} for neural machine translation (NMT).
no code implementations • EACL 2017 • Gongye Jin, Daisuke Kawahara, Sadao Kurohashi
To compensate the deficiency of the surface case frames, we compile deep case frames from automatic semantic roles.
no code implementations • MTSummit 2017 • Raj Dabre, Fabien Cromieres, Sadao Kurohashi
In this paper, we explore a simple solution to "Multi-Source Neural Machine Translation" (MSNMT) which only relies on preprocessing a N-way multilingual corpus without modifying the Neural Machine Translation (NMT) architecture or training procedure.
no code implementations • 12 Jan 2017 • Chenhui Chu, Raj Dabre, Sadao Kurohashi
In this paper, we propose a novel domain adaptation method named "mixed fine tuning" for neural machine translation (NMT).
no code implementations • 12 Dec 2016 • Xun Wang, Katsuhito Sudoh, Masaaki Nagata, Tomohide Shibata, Daisuke Kawahara, Sadao Kurohashi
This paper introduces a novel neural network model for question answering, the \emph{entity-based memory network}.
1 code implementation • WS 2016 • Fabien Cromieres, Chenhui Chu, Toshiaki Nakazawa, Sadao Kurohashi
We report very good translation results, especially when using neural MT for Chinese-to-Japanese translation.
no code implementations • COLING 2016 • Mo Shen, Wingmui Li, HyunJeong Choe, Chenhui Chu, Daisuke Kawahara, Sadao Kurohashi
In this paper, we propose a new annotation approach to Chinese word segmentation, part-of-speech (POS) tagging and dependency labelling that aims to overcome the two major issues in traditional morphology-based annotation: Inconsistency and data sparsity.
no code implementations • WS 2016 • Toshiaki Nakazawa, Chenchen Ding, Hideya Mino, Isao Goto, Graham Neubig, Sadao Kurohashi
For the WAT2016, 15 institutions participated in the shared tasks.
no code implementations • WS 2016 • Naoki Otani, Daisuke Kawahara, Sadao Kurohashi, Nobuhiro Kaji, Manabu Sassano
Commonsense knowledge is essential for fully understanding language in many situations.
no code implementations • WS 2016 • Chenhui Chu, Toshiaki Nakazawa, Daisuke Kawahara, Sadao Kurohashi
Treebanks are curial for natural language processing (NLP).
no code implementations • 7 Jun 2016 • Chenhui Chu, Sadao Kurohashi
As alignment links are not given between English sentences and Abstract Meaning Representation (AMR) graphs in the AMR annotation, automatic alignment becomes indispensable for training an AMR parser.
no code implementations • LREC 2016 • Chenhui Chu, Sadao Kurohashi
Out-of-vocabulary (OOV) word is a crucial problem in statistical machine translation (SMT) with low resources.
no code implementations • LREC 2016 • Antoine Bourlon, Chenhui Chu, Toshiaki Nakazawa, Sadao Kurohashi
Sentence alignment is a task that consists in aligning the parallel sentences in a translated article pair.
no code implementations • LREC 2016 • Toshiaki Nakazawa, Manabu Yaguchi, Kiyotaka Uchimoto, Masao Utiyama, Eiichiro Sumita, Sadao Kurohashi, Hitoshi Isahara
In this paper, we describe the details of the ASPEC (Asian Scientific Paper Excerpt Corpus), which is the first large-size parallel corpus of scientific paper domain.
no code implementations • LREC 2016 • Chenhui Chu, Raj Dabre, Sadao Kurohashi
Parallel corpora are crucial for machine translation (MT), however they are quite scarce for most language pairs and domains.
no code implementations • LREC 2014 • John Richardson, Toshiaki Nakazawa, Sadao Kurohashi
In this paper we present a bilingual transliteration lexicon of 170K Japanese-English technical terms in the scientific domain.
no code implementations • LREC 2014 • Tomohide Shibata, Shotaro Kohama, Sadao Kurohashi
This paper presents a large scale database of strongly-related events in Japanese, which has been acquired with our proposed method (Shibata and Kurohashi, 2011).
no code implementations • LREC 2014 • Chenhui Chu, Toshiaki Nakazawa, Sadao Kurohashi
Using the system, we construct a Chinese―Japanese parallel corpus with more than 126k highly accurate parallel sentences from Wikipedia.
no code implementations • LREC 2014 • Gongye Jin, Daisuke Kawahara, Sadao Kurohashi
The identification of various types of relations is a necessary step to allow computers to understand natural language text.
no code implementations • LREC 2014 • Tomoko Izumi, Tomohide Shibata, Hisako Asano, Yoshihiro Matsuo, Sadao Kurohashi
We construct a large corpus of Japanese predicate phrases for synonym-antonym relations.
no code implementations • LREC 2012 • Chenhui Chu, Toshiaki Nakazawa, Sadao Kurohashi
Chinese characters are used both in Japanese and Chinese, which are called Kanji and Hanzi respectively.