---
title: "Shenzhen–Dongguan — research institutions and their papers"
description: "Shenzhen–Dongguan (China): 9 institutions with papers on Elamur Research — 4 universities, 2 labs and research institutes, 3 companies…"
canonical: "https://research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/"
---
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[home](https://md.research.elamur.ai/free/en/) / [institutions](https://md.research.elamur.ai/free/en/orgs/) / [agglomerations](https://md.research.elamur.ai/free/en/agglomerations/) / Shenzhen–Dongguan

# Shenzhen–Dongguan

Agglomeration [China](https://md.research.elamur.ai/free/en/countries/china/) · metro population 18,966,068 (the Guangzhou functional urban area, GHSL 2015)

**9** institutions with a page**142** works in our library**41,024** citations of their works

## Institutions (9)

4 universities, 2 labs and research institutes, 3 companies.

### 🎓 Universities (4)

1. **[Chinese University of Hong Kong, Shenzhen](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong-shenzhen/)**University · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*17 works · 2,364 citations*
2. **[Shenzhen Research Institute of Big Data](https://md.research.elamur.ai/free/en/universities/shenzhen-research-institute-of-big-data/)**University · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*11 works · 1,615 citations*
3. **[Tsinghua Shenzhen International Graduate School](https://md.research.elamur.ai/free/en/universities/tsinghua-shenzhen-international-graduate-school/)**University · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*8 works · 2,860 citations*
4. **[Southern University of Science and Technology](https://md.research.elamur.ai/free/en/universities/southern-university-of-science-and-technology/)**University · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*4 works · 1,252 citations*

### 🔬 Labs and research institutes (2)

1. **[Peng Cheng Laboratory](https://md.research.elamur.ai/free/en/labs/peng-cheng-laboratory/)**Research institute · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*18 works · 2,349 citations*
2. **[Shenzhen Institutes of Advanced Technology](https://md.research.elamur.ai/free/en/labs/shenzhen-institutes-of-advanced-technology/)**Research institute · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*12 works · 2,431 citations*

### 🏢 Companies (3)

1. **[Tencent](https://md.research.elamur.ai/free/en/companies/tencent/)**Company · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*66 works · 17,945 citations*
2. **[Huawei Technologies](https://md.research.elamur.ai/free/en/companies/huawei-technologies/)**Company · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*29 works · 9,991 citations*
3. **[Ping An](https://md.research.elamur.ai/free/en/companies/ping-an/)**Company · Shenzhen, [China](https://md.research.elamur.ai/free/en/countries/china/)*2 works · 217 citations*

## Works in our library (142)

Works of its institutions, the most cited first.

1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,222 citations*
2. **[Parameter-efficient fine-tuning of large-scale pre-trained language models](https://md.research.elamur.ai/free/en/papers/ding-2023-parameter-efficient-fine-tuning-large/) [Nature Machine Intelligence](https://md.research.elamur.ai/free/en/venues/nature-machine-intelligence/)**Ning Ding, Yujia Qin, Guang You Yang, et al.*2023 · 1,324 citations*
3. **[Neural Responding Machine for Short-Text Conversation](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lifeng Shang, Zhengdong Lu, Hang Li*2015 · 1,253 citations*
4. **[Recurrent Attention Network on Memory for Aspect Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/chen-2017-recurrent-attention-network-memory-aspect/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peng Chen, Zhongqian Sun, Lidong Bing, et al.*2017 · 1,117 citations*
5. [**A Survey on Multimodal Large Language Models arXiv:2306.13549**Shukang Yin, Chaoyou Fu, Sirui Zhao, et al.*2023 · 1,062 citations*](https://md.research.elamur.ai/free/en/papers/yin-2023-survey-multimodal-large-language-models/)
6. **[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*
7. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 966 citations*
8. **[Modeling Coverage for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al.*2016 · 934 citations*
9. **[Generating Radiology Reports via Memory-driven Transformer](https://md.research.elamur.ai/free/en/papers/chen-2020-generating-radiology-reports-memory-driven/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhihong Chen, Yan Song, Tsung-Hui Chang, et al.*2020 · 710 citations*
10. **[Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate](https://md.research.elamur.ai/free/en/papers/liang-2023-encouraging-divergent-thinking-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tian Liang, Zhiwei He, Wenxiang Jiao, et al.*2023 · 643 citations*
11. [**Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine arXiv:2301.08745**Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, et al.*2023 · 631 citations*](https://md.research.elamur.ai/free/en/papers/jiao-2023-chatgpt-good-translator-yes-gpt/)
12. **[Transformation Networks for Target-Oriented Sentiment Classification](https://md.research.elamur.ai/free/en/papers/li-2018-transformation-networks-target-oriented-sentiment/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Li, Lidong Bing, Wai Lam, et al.*2018 · 597 citations*
13. [**ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs arXiv:2307.16789**Yujia Qin, Shihao Liang, Yining Ye, et al.*2023 · 566 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-toolllm-facilitating-large-language-models/)
14. [**MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models arXiv:2309.12284**Longhui Yu, Weisen Jiang, Han Shi, et al.*2023 · 556 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-metamath-bootstrap-your-own-mathematical/)
15. **[MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/fu-2023-mme-comprehensive-evaluation-benchmark-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Chaoyou Fu, Peixian Chen, Yunhang Shen, et al.*2023 · 529 citations*
16. **[CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X](https://md.research.elamur.ai/free/en/papers/zheng-2023-codegeex-pre-trained-model-code/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Qinkai Zheng, Xiao Xia, Xu Zou, et al.*2023 · 462 citations*
17. **[MVBench: A Comprehensive Multi-modal Video Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/li-2023-mvbench-comprehensive-multi-modal-video/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Kunchang Li, Yali Wang, Yinan He, et al.*2023 · 442 citations*
18. **[Directional Skip-Gram: Explicitly Distinguishing Left and Right Context for Word Embeddings](https://md.research.elamur.ai/free/en/papers/song-2018-directional-skip-gram-explicitly-distinguishing/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yan Song, Shuming Shi, Jing Li, et al.*2018 · 442 citations*
19. [**Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection arXiv:2303.05499**Shilong Liu, Zhaoyang Zeng, Tianhe Ren, et al.*2023 · 430 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-grounding-dino-marrying-dino-grounded/)
20. **[Event Extraction as Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/liu-2020-event-extraction-as-machine-reading/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jian Liu, Yubo Chen, Kang Liu, et al.*2020 · 420 citations*
21. **[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*
22. **[Towards Emotional Support Dialog Systems](https://md.research.elamur.ai/free/en/papers/liu-2021-emotional-support-dialog-systems/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siyang Liu, Chujie Zheng, Orianna Demasi, et al.*2021 · 391 citations*
23. **[Deep Semantic Role Labeling with Self-Attention](https://md.research.elamur.ai/free/en/papers/tan-2017-deep-semantic-role-labeling-self/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Zhixing Tan, Mingxuan Wang, Jun Xie, et al.*2017 · 387 citations*
24. **[FastBERT: a Self-distilling BERT with Adaptive Inference Time](https://md.research.elamur.ai/free/en/papers/liu-2020-fastbert-self-distilling-bert-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weijie Liu, Peng Zhou, Zhiruo Wang, et al.*2020 · 378 citations*
25. **[Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](https://md.research.elamur.ai/free/en/papers/lu-2021-text2event-controllable-sequence-structure-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaojie Lu, Hongyu Lin, Jin Xu, et al.*2021 · 370 citations*

[See all 142 works in Shenzhen–Dongguan →](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/works/)

## Works by year

### 2020s

[**2026** 5 works Works of Shenzhen–Dongguan from 2026](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2026/) · [**2025** 3 works Works of Shenzhen–Dongguan from 2025](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2025/) · [**2024** 20 works Works of Shenzhen–Dongguan from 2024](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2024/) · [**2023** 36 works Works of Shenzhen–Dongguan from 2023](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2023/) · [**2022** 17 works Works of Shenzhen–Dongguan from 2022](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2022/) · [**2021** 18 works Works of Shenzhen–Dongguan from 2021](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2021/) · [**2020** 15 works Works of Shenzhen–Dongguan from 2020](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2020/)

### 2010s

[**2019** 11 works Works of Shenzhen–Dongguan from 2019](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2019/) · [**2018** 8 works Works of Shenzhen–Dongguan from 2018](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2018/) · [**2017** 6 works Works of Shenzhen–Dongguan from 2017](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2017/) · [**2016** 2 works Works of Shenzhen–Dongguan from 2016](https://md.research.elamur.ai/free/en/agglomerations/shenzhen-dongguan/year/2016/) · [**2015** 1 work Works of Shenzhen–Dongguan from 2015](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/)

## Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 28 The field of science this work belongs to (OpenAlex fields).[Computer Science · 142 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 127 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 139 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 127 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 40 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 8 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Social Sciences · 7 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Medicine · 4 works](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Mathematics · 4 works](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Computational Theory and Mathematics · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Health Informatics · 4 works](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) · [Safety Research · 4 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/safety-research/) · [Psychology · 2 works](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Control and Systems Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/control-and-systems-engineering/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/)+13 more

🧭 Topics 30 Research subjects and languages the work is about.[Language models & pretraining · 40 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Machine translation · 20 works](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Sentiment & emotion · 10 works](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Evaluation & benchmarks · 19 works](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Vision & language · 11 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Information extraction · 7 works](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Reasoning · 10 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Knowledge graphs & ontologies · 4 works](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Question answering · 6 works](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Efficient models & compression · 3 works](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Text generation · 3 works](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Code & programming languages · 3 works](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Summarization · 2 works](https://md.research.elamur.ai/free/en/topics/summarization/) · [Dialogue systems · 6 works](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Multilingual & cross-lingual NLP · 3 works](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/)+15 more

💡 Concepts 3 Key ideas and methods explained on our concept pages.[Language model · 1 work](https://md.research.elamur.ai/free/en/concepts/language-model/) · [Semantic role labeling · 1 work](https://md.research.elamur.ai/free/en/concepts/semantic-role-labeling/) · [Ontology engineering · 1 work](https://md.research.elamur.ai/free/en/concepts/ontology-engineering/)

Agglomerations: the GHSL Urban Centre Database 2025; populations: the GHSL functional urban areas 2015 (urban centre and commuting zone), else the urban centre, as each page says (European Commission, Joint Research Centre, CC BY 4.0). An institution belongs to the urban centre its coordinates (ROR, OpenAlex) fall in, or one within 5 km. Land: Natural Earth.

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

Updated 24 October 2026