---
title: "Guangzhou–Foshan — research institutions and their papers"
description: "Guangzhou–Foshan (China): 3 institutions with papers on Elamur Research — 3 universities — and 11,439 citations of their works."
canonical: "https://research.elamur.ai/free/en/agglomerations/guangzhou-foshan/"
---
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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/) / Guangzhou–Foshan

# Guangzhou–Foshan

Agglomeration [China](https://md.research.elamur.ai/free/en/countries/china/) · metro population 23,506,852 (the Guangzhou functional urban area, GHSL 2015)

**3** institutions with a page**38** works in our library**11,439** citations of their works

## Institutions (3)

3 universities.

### 🎓 Universities (3)

1. **[Sun Yat-sen University](https://md.research.elamur.ai/free/en/universities/sun-yat-sen-university/)**University · Guangzhou, [China](https://md.research.elamur.ai/free/en/countries/china/)*23 works · 8,980 citations*
2. **[The Hong Kong University of Science and Technology (Guangzhou)](https://md.research.elamur.ai/free/en/universities/the-hong-kong-university-of-science-and-technology-guangzhou/)**University · Guangzhou, [China](https://md.research.elamur.ai/free/en/countries/china/)*7 works · 1,026 citations*
3. **[South China University of Technology](https://md.research.elamur.ai/free/en/universities/south-china-university-of-technology/)**University · Guangzhou, [China](https://md.research.elamur.ai/free/en/countries/china/)*8 works · 1,433 citations*

## Works in our library (38)

Works of its institutions, the most cited first.

1. **[CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,960 citations*
2. **[Relational Graph Attention Network for Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/wang-2020-relational-graph-attention-network-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Wang, Weizhou Shen, Yunyi Yang, et al.*2020 · 776 citations*
3. **[LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking](https://md.research.elamur.ai/free/en/papers/huang-2022-layoutlmv3-pre-training-document-ai/) [ACM International Conference on Multimedia (ACM MM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-multimedia-acm-mm/)**Yupan Huang, Tengchao Lv, Lei Cui, et al.*2022 · 774 citations*
4. **[UniXcoder: Unified Cross-Modal Pre-training for Code Representation](https://md.research.elamur.ai/free/en/papers/guo-2022-unixcoder-unified-cross-modal-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daya Guo, Shuai Lu, Nan Duan, et al.*2022 · 768 citations*
5. **[Knowledge Graph and Text Jointly Embedding](https://md.research.elamur.ai/free/en/papers/wang-2014-knowledge-graph-text-jointly-embedding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Wang, Jianwen Zhang, Jianlin Feng, et al.*2014 · 457 citations*
6. [**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/)
7. **[Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms](https://md.research.elamur.ai/free/en/papers/shen-2018-baseline-needs-more-love-simple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dinghan Shen, Guoyin Wang, Wenlin Wang, et al.*2018 · 385 citations*
8. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
9. **[Directed Acyclic Graph Network for Conversational Emotion Recognition](https://md.research.elamur.ai/free/en/papers/shen-2021-directed-acyclic-graph-network-conversational/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weizhou Shen, Siyue Wu, Yunyi Yang, et al.*2021 · 345 citations*
10. [**GraphCodeBERT: Pre-training Code Representations with Data Flow arXiv:2009.08366**Daya Guo, Shuo Ren, Shuai Lu, et al.*2021 · 331 citations*](https://md.research.elamur.ai/free/en/papers/guo-2021-graphcodebert-pre-training-code-representations/)
11. **[AugGPT: Leveraging ChatGPT for Text Data Augmentation](https://md.research.elamur.ai/free/en/papers/dai-2023-auggpt-leveraging-chatgpt-text-data/) [IEEE Transactions on Big Data](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-big-data/)**Haixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li*2023 · 306 citations*
12. **[OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 297 citations*
13. **[Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data](https://md.research.elamur.ai/free/en/papers/xu-2023-baize-open-source-chat-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Canwen Xu, Daya Guo, Nan Duan, et al.*2023 · 296 citations*
14. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning arXiv:2309.05653**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
15. **[Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://md.research.elamur.ai/free/en/papers/cao-2023-assessing-cross-cultural-alignment-between/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Yong Cao, Li Zhou, Seolhwa Lee, et al.*2023 · 278 citations*
16. **[A Study of Reinforcement Learning for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wu-2018-study-reinforcement-learning-neural-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lijun Wu, Fei Tian, Tao Qin, et al.*2018 · 234 citations*
17. **[Reasoning Over Semantic-Level Graph for Fact Checking](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wanjun Zhong, Jingjing Xu, Duyu Tang, et al.*2020 · 221 citations*
18. **[GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2021-geoqa-geometric-question-answering-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaqi Chen, Jianheng Tang, Jinghui Qin, et al.*2021 · 183 citations*
19. **[Soft Contextual Data Augmentation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gao-2019-soft-contextual-data-augmentation-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fei Gao, Jinhua Zhu, Lijun Wu, et al.*2019 · 172 citations*
20. **[Target-Guided Open-Domain Conversation](https://md.research.elamur.ai/free/en/papers/tang-2019-target-guided-open-domain-conversation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, et al.*2019 · 166 citations*
21. **[SemEval-2020 Task 4: Commonsense Validation and Explanation](https://md.research.elamur.ai/free/en/papers/wang-2020-semeval-2020-task-4-commonsense/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Cunxiang Wang, Shuailong Liang, Yili Jin, et al.*2020 · 157 citations*
22. **[GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems](https://md.research.elamur.ai/free/en/papers/huang-2020-grade-automatic-graph-enhanced-coherence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lishan Huang, Zheng Ye, Jinghui Qin, et al.*2020 · 144 citations*
23. [**Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning arXiv:2105.04165**Pan Lu, Ran Gong, Shibiao Jiang, et al.*2021 · 134 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-inter-gps-interpretable-geometry-problem/)
24. **[A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems](https://md.research.elamur.ai/free/en/papers/yi-2024-survey-recent-advances-llm-based/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Zihao Yi, Jiarui Ouyang, Zhe Xu, et al.*2024 · 129 citations*
25. **[UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression](https://md.research.elamur.ai/free/en/papers/chen-2022-unigeo-unifying-geometry-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaqi Chen, Tong Li, Jinghui Qin, et al.*2022 · 111 citations*

[See all 38 works in Guangzhou–Foshan →](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/works/)

## Works by year

### 2020s

[**2026** 1 work Works of Guangzhou–Foshan from 2026](https://md.research.elamur.ai/free/en/papers/chen-2026-auditing-discovery-claims-two/) · [**2024** 6 works Works of Guangzhou–Foshan from 2024](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2024/) · [**2023** 9 works Works of Guangzhou–Foshan from 2023](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2023/) · [**2022** 4 works Works of Guangzhou–Foshan from 2022](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2022/) · [**2021** 4 works Works of Guangzhou–Foshan from 2021](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2021/) · [**2020** 8 works Works of Guangzhou–Foshan from 2020](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2020/)

### 2010s

[**2019** 3 works Works of Guangzhou–Foshan from 2019](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2019/) · [**2018** 2 works Works of Guangzhou–Foshan from 2018](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2018/) · [**2014** 1 work Works of Guangzhou–Foshan from 2014](https://md.research.elamur.ai/free/en/papers/wang-2014-knowledge-graph-text-jointly-embedding/)

## Fields, topics and concepts

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

📚 Shelves 22 The field of science this work belongs to (OpenAlex fields).[Computer Science · 38 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 31 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 34 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 31 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 11 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Mathematics · 4 works](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [Computer Science Applications · 3 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-science-applications/) · [Computational Theory and Mathematics · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) · [Applied Mathematics · 3 works](https://md.research.elamur.ai/free/en/shelves/mathematics/applied-mathematics/) · [Social Sciences · 3 works](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [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/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/)+7 more

🧭 Topics 14 Research subjects and languages the work is about.[Code & programming languages · 4 works](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Language models & pretraining · 8 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Dialogue systems · 8 works](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Reasoning · 5 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Machine translation · 3 works](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Sentiment & emotion · 2 works](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Vision & language · 3 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Knowledge graphs & ontologies · 1 work](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Discourse analysis · 2 works](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Evaluation & benchmarks · 2 works](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Grammatical error correction & learner language · 1 work](https://md.research.elamur.ai/free/en/topics/grammatical-error-correction/) · [Speech act theory · 3 works](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [Efficient models & compression · 1 work](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/)

💡 Concepts 1 Key ideas and methods explained on our concept pages.[Minimum description length · 1 work](https://md.research.elamur.ai/free/en/concepts/minimum-description-length/)

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.

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Updated 24 October 2026