---
title: "Shenzhen–Dongguan — works of 2019 — Elamur Research"
description: "11 works of Shenzhen–Dongguan from 2019 in our library, the most cited first. Among them: K-BERT: Enabling Language Representation…"
canonical: "https://research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2019/"
---
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# Works of Shenzhen–Dongguan from 2019

11 works · the most cited first · [← Shenzhen–Dongguan](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/)

1. **[K-BERT: Enabling Language Representation with Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Weijie Liu, Peng Zhou, Zhe Zhao, et al.*2019 · 1,014 citations*
2. **[A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/jiang-2019-challenge-dataset-effective-models-aspect/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingnan Jiang, Lei Chen, Ruifeng Xu, et al.*2019 · 395 citations*
3. **[Bridging the Gap between Training and Inference for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2019-bridging-gap-between-training-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Zhang, Yang Feng, Fandong Meng, et al.*2019 · 299 citations*
4. **[GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification](https://md.research.elamur.ai/free/en/papers/zhou-2019-gear-graph-based-evidence-aggregating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jie Zhou, Xu Han, Cheng Yang, et al.*2019 · 288 citations*
5. **[Results of the WMT19 Metrics Shared Task: Segment-Level and Strong MT Systems Pose Big Challenges](https://md.research.elamur.ai/free/en/papers/ma-2019-results-wmt19-metrics-shared-task/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Qingsong Ma, Johnny Wei, Ondřej Bojar, et al.*2019 · 284 citations*
6. **[A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer](https://md.research.elamur.ai/free/en/papers/luo-2019-dual-reinforcement-learning-framework-unsupervised/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Fuli Luo, Peng Li, Jie Zhou, et al.*2019 · 266 citations*
7. **[EditNTS: An Neural Programmer-Interpreter Model for Sentence Simplification through Explicit Editing](https://md.research.elamur.ai/free/en/papers/dong-2019-editnts-neural-programmer-interpreter-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Dong, Zichao Li, Mehdi Rezagholizadeh, et al.*2019 · 242 citations*
8. **[BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://md.research.elamur.ai/free/en/papers/sharma-2019-bigpatent-large-scale-dataset-abstractive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eva Sharma, Chen Li, Lu Wang*2019 · 235 citations*
9. **[Improving Machine Reading Comprehension with General Reading Strategies](https://md.research.elamur.ai/free/en/papers/sun-2019-improving-machine-reading-comprehension-general/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kai Sun, Dian Yu, Dong Yu, et al.*2019 · 172 citations*
10. **[Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Sun, Dian Yu, Dong Yu, et al.*2019 · 133 citations*
11. **[One Model to Learn Both: Zero Pronoun Prediction and Translation](https://md.research.elamur.ai/free/en/papers/wang-2019-one-model-learn-both-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Longyue Wang, Zhaopeng Tu, Xing Wang, et al.*2019 · 41 citations*
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