---
title: "Greater Tokyo — works of 2016: 10 papers, the most cited first"
description: "10 works of Greater Tokyo from 2016 in our library, the most cited first. Among them: A Joint Many-Task Model: Growing a Neural Network…"
canonical: "https://research.elamur.ai/free/en/agglomerations/greater-tokyo/year/2016/"
---
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# Works of Greater Tokyo from 2016

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

1. **[A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks](https://md.research.elamur.ai/free/en/papers/hashimoto-2016-joint-many-task-model-growing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, et al.*2016 · 668 citations*
2. [**Adversarial Training Methods for Semi-Supervised Text Classification arXiv:1605.07725**Takeru Miyato, Andrew M. Dai, Ian Goodfellow*2016 · 427 citations*](https://md.research.elamur.ai/free/en/papers/miyato-2016-adversarial-training-methods-semi-supervised/)
3. **[Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation](https://md.research.elamur.ai/free/en/papers/yamada-2016-joint-learning-embedding-words-entities/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2016 · 427 citations*
4. **[Controlling Output Length in Neural Encoder-Decoders](https://md.research.elamur.ai/free/en/papers/kikuchi-2016-controlling-output-length-neural-encoder/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuta Kikuchi, Graham Neubig, Ryohei Sasano, et al.*2016 · 323 citations*
5. **[Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't.](https://md.research.elamur.ai/free/en/papers/gladkova-2016-analogy-based-detection-morphological-semantic/) [NAACL Student Research Workshop](https://md.research.elamur.ai/free/en/venues/naacl-student-research-workshop/)**Anna Gladkova, Aleksandr Drozd, Satoshi Matsuoka*2016 · 312 citations*
6. **[ASPEC: Asian Scientific Paper Excerpt Corpus](https://md.research.elamur.ai/free/en/papers/nakazawa-2016-aspec-asian-scientific-paper-excerpt/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Toshiaki Nakazawa, Manabu Yaguchi, Kiyotaka Uchimoto, et al.*2016 · 245 citations*
7. **[Neural Machine Translation with Supervised Attention](https://md.research.elamur.ai/free/en/papers/liu-2016-neural-machine-translation-supervised-attention/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Lemao Liu, Masao Utiyama, Andrew Finch, et al.*2016 · 84 citations*
8. **[Intra-Sentential Subject Zero Anaphora Resolution using Multi-Column Convolutional Neural Network](https://md.research.elamur.ai/free/en/papers/iida-2016-intra-sentential-subject-zero-anaphora/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryu Iida, Kentaro Torisawa, Jong-Hoon Oh, et al.*2016 · 51 citations*
9. **[BCCWJ-DepPara: A Syntactic Annotation Treebank on the ‘Balanced Corpus of Contemporary Written Japanese'](https://md.research.elamur.ai/free/en/papers/asahara-2016-bccwj-deppara-syntactic-annotation-treebank/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Masayuki Asahara, Yuji Matsumoto*2016 · 23 citations*
10. **[Analysis of English Spelling Errors in a Word-Typing Game](https://md.research.elamur.ai/free/en/papers/tachibana-2016-analysis-english-spelling-errors-word/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ryuichi Tachibana, Mamoru Komachi*2016 · 9 citations*
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