---
title: "China — research institutions, scientists and papers"
description: "China: 83 institutions with papers in our library in 20 agglomerations, 599 people with a page, 616 works, 603,513 citations."
canonical: "https://research.elamur.ai/free/en/countries/china/"
---
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# China

Country 83 institutions in 20 agglomerations · [all countries](https://md.research.elamur.ai/free/en/countries/)

[**83** institutions with a page](https://md.research.elamur.ai/free/en/countries/china/#institutions) · [**20** agglomerations](https://md.research.elamur.ai/free/en/countries/china/#agglomerations) · [**599** people with a page](https://md.research.elamur.ai/free/en/countries/china/#authors) · [**616** works in our library](https://md.research.elamur.ai/free/en/countries/china/#works) · [**603,513** citations of their works](https://md.research.elamur.ai/free/en/countries/china/#works)

## About

### Profile

This is the library's directory of research institutions in China. It gathers the universities, laboratories, companies and government bodies whose researchers have written at least two of the papers held on this site. Institutions are ordered by how much the work their scientists did there has been cited. The list covers only the papers and people on this site, so it shows China's presence within this library's collection. It is not a census of Chinese research. The first page runs from [Tsinghua University](https://md.research.elamur.ai/free/en/universities/tsinghua-university/) to [Tianjin University](https://md.research.elamur.ai/free/en/universities/tianjin-university/), and a second page continues with further institutions. Each entry links to its own page, and the [full directory of institutions](https://md.research.elamur.ai/free/en/orgs/) groups organisations of every kind across all countries.

Four kinds of institution share the list: universities, companies, research institutes and one government body. Their mix is the most useful feature of the page. Academic, corporate and state-funded research appear side by side, and companies sit close to the top among the universities. Many of the institute and laboratory names refer to artificial intelligence, computing, automation, software and information science. Together with the corporate laboratories, they suggest that the Chinese work here is concentrated in computing-related research. The directory does not break this down by topic, so a reader who wants a field-by-field picture should open the individual pages.

### Universities

Universities make up the largest group, and they hold the first place in the order. Tsinghua University in Beijing heads the list. On this site its scientists have one of the largest bodies of work and one of the largest citation totals of any Chinese institution. [Peking University](https://md.research.elamur.ai/free/en/universities/peking-university/), also in Beijing, follows a few places down. Like Tsinghua, it pairs a broad collection of papers with heavy citation.

Shanghai is represented near the top by [Fudan University](https://md.research.elamur.ai/free/en/universities/fudan-university/) and [Shanghai Jiao Tong University](https://md.research.elamur.ai/free/en/universities/shanghai-jiao-tong-university/). [Renmin University of China](https://md.research.elamur.ai/free/en/universities/renmin-university-of-china/) in Beijing and [Harbin Institute of Technology](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/) in the north-east also appear in the upper part of the list. Harbin's contribution is one of the larger sets of works among the universities.

[University of Science and Technology of China](https://md.research.elamur.ai/free/en/universities/university-of-science-and-technology-of-china/) in Hefei shows how citation and volume can diverge. Its set of works in our library is modest. Even so, its citation total is the highest of any Chinese institution listed, which means a few papers by its scientists have been cited very widely. [Xi'an Jiaotong University](https://md.research.elamur.ai/free/en/universities/xi-an-jiaotong-university/) shows a similar pattern even more sharply. Only a small handful of its papers appear here, yet they carry a citation total that exceeds that of many institutions with far larger collections. [Jilin University](https://md.research.elamur.ai/free/en/universities/jilin-university/) in Changchun likewise combines a small number of works with a substantial citation count.

Further down, the universities spread across the country. [Zhejiang University](https://md.research.elamur.ai/free/en/universities/zhejiang-university/) and [Westlake University](https://md.research.elamur.ai/free/en/universities/westlake-university/) represent Hangzhou. Nanjing is represented by [Nanjing University](https://md.research.elamur.ai/free/en/universities/nanjing-university/), and Guangzhou by [Sun Yat-sen University](https://md.research.elamur.ai/free/en/universities/sun-yat-sen-university/). [Soochow University](https://md.research.elamur.ai/free/en/universities/soochow-university/) in Suzhou has a comparatively large set of works, though they are less heavily cited than those of the institutions around it.

Beijing adds [Beihang University](https://md.research.elamur.ai/free/en/universities/beihang-university/), [Beijing Institute of Technology](https://md.research.elamur.ai/free/en/universities/beijing-institute-of-technology/), [Beijing University of Posts and Telecommunications](https://md.research.elamur.ai/free/en/universities/beijing-university-of-posts-and-telecommunications/) and [Beijing Normal University](https://md.research.elamur.ai/free/en/universities/beijing-normal-university/). It also adds the [University of Chinese Academy of Sciences](https://md.research.elamur.ai/free/en/universities/university-of-chinese-academy-of-sciences/), the teaching arm linked to the national academy.

Other regional universities appear lower on the first page. They include [East China Normal University](https://md.research.elamur.ai/free/en/universities/east-china-normal-university/) in Shanghai, [Huazhong University of Science and Technology](https://md.research.elamur.ai/free/en/universities/huazhong-university-of-science-and-technology/) in Wuhan and [Xiamen University](https://md.research.elamur.ai/free/en/universities/xiamen-university/). [Northeastern University](https://md.research.elamur.ai/free/en/universities/northeastern-university-cn/) in Shenyang, [Sichuan University](https://md.research.elamur.ai/free/en/universities/sichuan-university/) in Chengdu and the [National University of Defense Technology](https://md.research.elamur.ai/free/en/universities/national-university-of-defense-technology/) in Changsha also appear. Wuhan University and Tianjin University close the first page.

Several entries are campuses or branches of larger systems in southern China. The [Chinese University of Hong Kong, Shenzhen](https://md.research.elamur.ai/free/en/universities/chinese-university-of-hong-kong-shenzhen/) and [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/) appear under their own names. So does the [Tsinghua Shenzhen International Graduate School](https://md.research.elamur.ai/free/en/universities/tsinghua-shenzhen-international-graduate-school/), listed separately from its parent university in Beijing. Because these appear as distinct entries, work done at a Shenzhen or Guangzhou campus is credited to that campus on this site rather than folded into the main institution.

### Companies

The prominence of companies is a distinctive feature of the Chinese list. Three of the first four places go to corporate research organisations.

[DeepSeek](https://md.research.elamur.ai/free/en/companies/deepseek/), based in Hangzhou, stands second, directly behind Tsinghua. Its body of work in our library is very small. Its position suggests that its few papers have drawn heavy attention relative to their number.

[Alibaba Group](https://md.research.elamur.ai/free/en/companies/alibaba-group/), also in Hangzhou, comes third. Its research unit [Alibaba DAMO Academy](https://md.research.elamur.ai/free/en/companies/alibaba-damo-academy/) is listed separately further down. [Ant Group](https://md.research.elamur.ai/free/en/companies/ant-group/), another Hangzhou company, appears near the bottom of the first page with a small set of works.

[Microsoft Research Asia](https://md.research.elamur.ai/free/en/companies/microsoft-research-asia/) in Beijing holds fourth place. It is a company laboratory whose citation total on this site is among the very highest of all the Chinese entries. That indicates papers from this laboratory have been widely taken up by later research.

Shenzhen supplies two large corporate contributors, [Tencent](https://md.research.elamur.ai/free/en/companies/tencent/) and [Huawei Technologies](https://md.research.elamur.ai/free/en/companies/huawei-technologies/). Each has a sizeable collection of works here. Beijing adds [Baidu](https://md.research.elamur.ai/free/en/companies/baidu/), [ByteDance](https://md.research.elamur.ai/free/en/companies/bytedance/), [Sensetime](https://md.research.elamur.ai/free/en/companies/sensetime/) and [Meituan](https://md.research.elamur.ai/free/en/companies/meituan/). Meituan's few papers carry more citations than the works of several larger institutions near it in the order.

Taken together, the companies show a corporate research sector that is publishing actively among the works here. In this collection, the strongest Chinese research output comes from both academic and industrial settings, not from universities alone.

### Research institutes and the national academy

The [Chinese Academy of Sciences](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/) is the only government body on the first page. It appears in the upper third of the list with a broad body of work. Three of its Beijing institutes are listed separately: the [Institute of Automation](https://md.research.elamur.ai/free/en/labs/institute-of-automation/), the [Institute of Computing Technology](https://md.research.elamur.ai/free/en/labs/institute-of-computing-technology/) and the [Institute of Software](https://md.research.elamur.ai/free/en/labs/institute-of-software/). Of these, the Institute of Automation has the most cited work in our library. Its citation total is close to those of some of the large companies. The [Shenzhen Institutes of Advanced Technology](https://md.research.elamur.ai/free/en/labs/shenzhen-institutes-of-advanced-technology/) extend this network to the south.

A second group of research institutes carries names centred on artificial intelligence and information science. The [Shanghai Artificial Intelligence Laboratory](https://md.research.elamur.ai/free/en/labs/shanghai-artificial-intelligence-laboratory/) ranks among the top ten. It ranks above several long-established universities, and its collection of works is substantial. In Beijing, the [Beijing Academy of Artificial Intelligence](https://md.research.elamur.ai/free/en/labs/beijing-academy-of-artificial-intelligence/) and the [Beijing National Research Center for Information Science and Technology](https://md.research.elamur.ai/free/en/labs/beijing-national-research-center-for-information-science-and-technology/) both sit in the upper half of the list. The [Peng Cheng Laboratory](https://md.research.elamur.ai/free/en/labs/peng-cheng-laboratory/) in Shenzhen appears in the middle, with a moderate number of works that are less heavily cited.

These institutes show that, among the works here, a share of China's output comes from dedicated laboratories outside the university system. The academy's separately listed institutes also mean that its research appears both under the parent body and under individual units.

### Geography

The directory gives a city for every institution, and the cities trace a clear map of where the Chinese work in this library is done.

Beijing is the largest centre by a wide margin. It hosts the top-ranked university, Peking University and many of the city's other universities. It is also home to the national academy and its institutes, several artificial intelligence laboratories, and the companies Microsoft Research Asia, Baidu, ByteDance, Sensetime and Meituan.

Hangzhou forms a second cluster, notable for its companies. DeepSeek, Alibaba Group, Alibaba DAMO Academy and Ant Group are all listed there, alongside Zhejiang University and Westlake University. Shanghai contributes Fudan University, Shanghai Jiao Tong University, East China Normal University and the Shanghai Artificial Intelligence Laboratory.

Shenzhen combines industry and branch campuses. Tencent and Huawei Technologies sit there with the Peng Cheng Laboratory, the Shenzhen Institutes of Advanced Technology, the Chinese University of Hong Kong, Shenzhen and the Tsinghua Shenzhen International Graduate School.

Beyond these four cities, the list reaches many provincial centres through single universities. These include Harbin, Hefei, Nanjing, Guangzhou, Xi'an, Suzhou, Changchun, Wuhan, Xiamen, Shenyang, Chengdu, Changsha and Tianjin. In several of these cities, notably Hefei and Xi'an, one university accounts for a body of highly cited work in our library.

### Reading the list

The order on the page reflects the cited work done by each institution's scientists. It does not follow raw paper counts or raw citation totals. The two measures shown beside each name often disagree with each other and with the position.

DeepSeek ranks second with one of the smallest sets of works on the page. Microsoft Research Asia and the University of Science and Technology of China have citation totals larger than many institutions placed above them. Soochow University has a comparatively large collection but a lower place. Readers comparing institutions should therefore look at both figures on each entry, and at the works themselves on the institutional pages, rather than read the position alone.

The list also depends on how affiliations are recorded. Separate entries for parent bodies and their units mean that some research is visible in more than one place. This applies to the Chinese Academy of Sciences and its institutes, to Alibaba Group and its DAMO Academy, and to Tsinghua University and its Shenzhen school.

As the library adds papers, new institutions can join the list and the order can shift. The second page holds the institutions that currently fall below Tianjin University.

## Where

## Agglomerations (20)

1. [**Beijing**31 institutions*283,594 citations*](https://md.research.elamur.ai/free/en/agglomerations/beijing/)
2. [**Hefei**3 institutions*113,446 citations*](https://md.research.elamur.ai/free/en/agglomerations/hefei/)
3. [**Hong Kong**6 institutions*48,034 citations*](https://md.research.elamur.ai/free/en/agglomerations/hong-kong/)
4. [**Shanghai**9 institutions*44,531 citations*](https://md.research.elamur.ai/free/en/agglomerations/shanghai/)
5. [**Hangzhou**8 institutions*41,869 citations*](https://md.research.elamur.ai/free/en/agglomerations/hangzhou/)
6. [**Xi'an**4 institutions*36,769 citations*](https://md.research.elamur.ai/free/en/agglomerations/xi-an/)
7. [**Guangzhou**8 institutions*31,481 citations*](https://md.research.elamur.ai/free/en/agglomerations/guangzhou/)
8. [**Harbin**1 institution*25,250 citations*](https://md.research.elamur.ai/free/en/agglomerations/harbin/)
9. [**Guangzhou**3 institutions*9,428 citations*](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-cn/)
10. [**Nanjing**3 institutions*7,408 citations*](https://md.research.elamur.ai/free/en/agglomerations/nanjing/)
11. [**Changchun**1 institution*4,745 citations*](https://md.research.elamur.ai/free/en/agglomerations/changchun/)
12. [**Suzhou**2 institutions*4,163 citations*](https://md.research.elamur.ai/free/en/agglomerations/suzhou/)
13. [**Wuhan**2 institutions*3,794 citations*](https://md.research.elamur.ai/free/en/agglomerations/wuhan/)
14. [**Chengdu**2 institutions*2,446 citations*](https://md.research.elamur.ai/free/en/agglomerations/chengdu/)
15. [**Xiamen**1 institution*1,876 citations*](https://md.research.elamur.ai/free/en/agglomerations/xiamen-city/)
16. [**Shenyang**1 institution*1,800 citations*](https://md.research.elamur.ai/free/en/agglomerations/shenyang/)
17. [**Changsha**3 institutions*1,768 citations*](https://md.research.elamur.ai/free/en/agglomerations/changsha/)
18. [**Tianjin**2 institutions*1,270 citations*](https://md.research.elamur.ai/free/en/agglomerations/tianjin/)
19. [**Dalian**2 institutions*613 citations*](https://md.research.elamur.ai/free/en/agglomerations/dalian/)
20. [**Jinan**1 institution*519 citations*](https://md.research.elamur.ai/free/en/agglomerations/jinan/)

## Institutions (83)

### 🎓 Universities (54)

**[University of Science and Technology of China](https://md.research.elamur.ai/free/en/universities/university-of-science-and-technology-of-china/)**University · [Hefei](https://md.research.elamur.ai/free/en/agglomerations/hefei/), China*18 works · 109,489 citations*

**[Tsinghua University](https://md.research.elamur.ai/free/en/universities/tsinghua-university/)**University · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*92 works · 77,045 citations*

**[Xi'an Jiaotong University](https://md.research.elamur.ai/free/en/universities/xi-an-jiaotong-university/)**University · [Xi'an](https://md.research.elamur.ai/free/en/agglomerations/xi-an/), China*6 works · 35,595 citations*

**[Peking University](https://md.research.elamur.ai/free/en/universities/peking-university/)**University · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*74 works · 31,748 citations*

**[Harbin Institute of Technology](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/)**University · [Harbin](https://md.research.elamur.ai/free/en/agglomerations/harbin/), China*58 works · 25,250 citations*

### 🔬 Labs and research institutes (12)

**[Institute of Automation](https://md.research.elamur.ai/free/en/labs/institute-of-automation/)**Research institute · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*17 works · 13,299 citations*

**[Shanghai Artificial Intelligence Laboratory](https://md.research.elamur.ai/free/en/labs/shanghai-artificial-intelligence-laboratory/)**Research institute · [Shanghai](https://md.research.elamur.ai/free/en/agglomerations/shanghai/), China*29 works · 8,268 citations*

**[Beijing Academy of Artificial Intelligence](https://md.research.elamur.ai/free/en/labs/beijing-academy-of-artificial-intelligence/)**Research institute · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*12 works · 6,547 citations*

**[Beijing National Research Center for Information Science and Technology](https://md.research.elamur.ai/free/en/labs/beijing-national-research-center-for-information-science-and-technology/)**Research institute · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*11 works · 3,806 citations*

**[Shanghai Qi Zhi Institute](https://md.research.elamur.ai/free/en/labs/shanghai-qi-zhi-institute/)**Research institute · [Shanghai](https://md.research.elamur.ai/free/en/agglomerations/shanghai/), China*3 works · 2,926 citations*

### 🏢 Companies (15)

**[Microsoft Research Asia](https://md.research.elamur.ai/free/en/companies/microsoft-research-asia/)**Company · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*41 works · 57,263 citations*

**[Tencent](https://md.research.elamur.ai/free/en/companies/tencent/)**Company · [Shenzhen](https://md.research.elamur.ai/free/en/agglomerations/guangzhou/), China*40 works · 13,547 citations*

**[Baidu](https://md.research.elamur.ai/free/en/companies/baidu/)**Company · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*26 works · 11,874 citations*

**[Alibaba Group](https://md.research.elamur.ai/free/en/companies/alibaba-group/)**Company · [Hangzhou](https://md.research.elamur.ai/free/en/agglomerations/hangzhou/), China*39 works · 10,954 citations*

**[Huawei Technologies](https://md.research.elamur.ai/free/en/companies/huawei-technologies/)**Company · [Shenzhen](https://md.research.elamur.ai/free/en/agglomerations/guangzhou/), China*21 works · 8,831 citations*

### 🏛️ Government research bodies (2)

**[Chinese Academy of Sciences](https://md.research.elamur.ai/free/en/government/chinese-academy-of-sciences/)**Government body · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*51 works · 17,412 citations*

**[Beijing Institute for General Artificial Intelligence](https://md.research.elamur.ai/free/en/government/beijing-institute-for-general-artificial-intelligence/)**Government body · [Beijing](https://md.research.elamur.ai/free/en/agglomerations/beijing/), China*3 works · 457 citations*

[See all 83 institutions →](https://md.research.elamur.ai/free/en/countries/china/institutions/)

## People (599)

Authors with a page confirmed at its institutions, the most cited first.

[🧑‍🔬**Kaiming He** Microsoft Research Asia 4 papers here · 82,825 citations](https://md.research.elamur.ai/free/en/authors/kaiming-he/) · [🧑‍🔬**Jie Tang** Tsinghua University 12 papers here · 30,698 citations](https://md.research.elamur.ai/free/en/authors/jie-tang/) · [🧑‍🔬**Furu Wei** Microsoft Research Asia 27 papers here · 19,862 citations](https://md.research.elamur.ai/free/en/authors/furu-wei/) · [🧑‍🔬**Ming Zhou** Microsoft Research Asia 22 papers here · 18,849 citations](https://md.research.elamur.ai/free/en/authors/ming-zhou/) · [🧑‍🔬**Ting Liu** Harbin Institute of Technology 23 papers here · 18,454 citations](https://md.research.elamur.ai/free/en/authors/ting-liu/) · [🧑‍🔬**Bing Qin** Harbin Institute of Technology 18 papers here · 16,498 citations](https://md.research.elamur.ai/free/en/authors/bing-qin/) · [🧑‍🔬**Chong Zhang** Fudan University 2 papers here · 16,390 citations](https://md.research.elamur.ai/free/en/authors/chong-zhang/) · [🧑‍🔬**Zhiyuan Liu** Tsinghua University 23 papers here · 16,385 citations](https://md.research.elamur.ai/free/en/authors/zhiyuan-liu/) · [🧑‍🔬**Yue Zhang** Westlake University 32 papers here · 16,287 citations](https://md.research.elamur.ai/free/en/authors/yue-zhang/) · [🧑‍🔬**Maosong Sun** Tsinghua University 20 papers here · 15,081 citations](https://md.research.elamur.ai/free/en/authors/maosong-sun/) · [🧑‍🔬**Zhilin Yang** Tsinghua University 9 papers here · 13,681 citations](https://md.research.elamur.ai/free/en/authors/zhilin-yang/) · [🧑‍🔬**Xipeng Qiu** Fudan University 23 papers here · 13,270 citations](https://md.research.elamur.ai/free/en/authors/xipeng-qiu/)

[See all 599 people →](https://md.research.elamur.ai/free/en/countries/china/people/)

## Works in our library (616)

Works of its institutions, the most cited first.

1. [**Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks**Shaoqing Ren, Kaiming He, Ross Girshick, et al.*2015 · 64,743 citations*](https://md.research.elamur.ai/free/en/papers/ren-2015-faster-r-cnn-towards-real/)
2. [**Swin Transformer: Hierarchical Vision Transformer using Shifted Windows**Ze Liu, Yutong Lin, Yue Cao, et al.*2021 · 33,826 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-swin-transformer-hierarchical-vision-transformer/)
3. [**DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning**DeepSeek-AI, Daya Guo, Dejian Yang, et al.*2025 · 4,593 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-r1-incentivizing-reasoning-capability/)
4. [**SimCSE: Simple Contrastive Learning of Sentence Embeddings**Tianyu Gao, Xingcheng Yao, Danqi Chen*2021 · 3,921 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-simcse-simple-contrastive-learning-sentence/)
5. [**A Survey on Evaluation of Large Language Models**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,640 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/)
6. [**A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,221 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/)
7. [**CodeBERT: A Pre-Trained Model for Programming and Natural Languages**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,954 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/)
8. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
9. [**Attention-based LSTM for Aspect-level Sentiment Classification**Yequan Wang, Minlie Huang, Xiaoyan Zhu, et al.*2016 · 2,609 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-attention-based-lstm-aspect-level/)
10. [**A Survey on Large Language Model based Autonomous Agents**Lei Wang, Chen Ma, Xueyang Feng, et al.*2023 · 2,263 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-large-language-model-based/)
11. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,013 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
12. [**Knowledge Graph Embedding via Dynamic Mapping Matrix**Guoliang Ji, Shizhu He, Liheng Xu, et al.*2015 · 1,936 citations*](https://md.research.elamur.ai/free/en/papers/ji-2015-knowledge-graph-embedding-dynamic-mapping/)
13. [**Pre-trained Models for Natural Language Processing: A Survey**Xipeng Qiu, Tianxiang Sun, Yige Xu, et al.*2020 · 1,740 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2020-pre-trained-models-natural-language/)
14. [**Document Modeling with Gated Recurrent Neural Network for Sentiment Classification**Duyu Tang, Bing Qin, Ting Liu*2015 · 1,675 citations*](https://md.research.elamur.ai/free/en/papers/tang-2015-document-modeling-gated-recurrent-neural/)
15. [**Relation Classification via Convolutional Deep Neural Network**Daojian Zeng, Kang Liu, Siwei Lai, et al.*2014 · 1,659 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2014-relation-classification-convolutional-deep-neural/)
16. [**SemEval-2016 Task 5: Aspect Based Sentiment Analysis**Maria Pontiki, Dimitris Galanis, Haris Papageorgiou, et al.*2016 · 1,656 citations*](https://md.research.elamur.ai/free/en/papers/pontiki-2016-semeval-2016-task-5-aspect/)
17. [**Retrieval-Augmented Generation for Large Language Models: A Survey**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,647 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
18. [**Deep Speech: Scaling up end-to-end speech recognition**Awni Hannun, Carl Case, Jared Casper, et al.*2014 · 1,575 citations*](https://md.research.elamur.ai/free/en/papers/hannun-2014-deep-speech-scaling-up-end/)
19. [**Unifying Large Language Models and Knowledge Graphs: A Roadmap**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/)
20. [**VisualBERT: A Simple and Performant Baseline for Vision and Language**Liunian Harold Li, Mark Yatskar, Da Yin, et al.*2019 · 1,510 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-visualbert-simple-performant-baseline-vision/)
21. [**Pre-Training with Whole Word Masking for Chinese BERT**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2019 · 1,485 citations*](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/)
22. [**GLM: General Language Model Pretraining with Autoregressive Blank Infilling**Zhengxiao Du, Yujie Qian, Xiao Liu, et al.*2022 · 1,449 citations*](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/)
23. [**TVM: An Automated End-to-End Optimizing Compiler for Deep Learning**Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al.*2018 · 1,371 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/)
24. [**brat: a Web-based Tool for NLP-Assisted Text Annotation**Pontus Stenetorp, Sampo Pyysalo, Goran Topić, et al.*2012 · 1,368 citations*](https://md.research.elamur.ai/free/en/papers/stenetorp-2012-brat-web-based-tool-nlp/)
25. [**Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification**Duyu Tang, Furu Wei, Nan Yang, et al.*2014 · 1,341 citations*](https://md.research.elamur.ai/free/en/papers/tang-2014-learning-sentiment-specific-word-embedding/)

[See all 616 works →](https://md.research.elamur.ai/free/en/countries/china/works/)

## Topics

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

[Language models & pretraining (176)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Sentiment & emotion (53)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Reasoning (51)](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Discourse analysis (49)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Evaluation & benchmarks (48)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Machine translation (46)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Vision & language (40)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Coreference resolution (27)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Dialogue systems (25)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Multilingual & cross-lingual NLP (23)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Information extraction (20)](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Information retrieval & search (20)](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Question answering (16)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Bias, fairness & safety (13)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Speech & spoken language (12)](https://md.research.elamur.ai/free/en/topics/speech/) · [Semitic languages (12)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Named entity recognition (9)](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/) · [Summarization (9)](https://md.research.elamur.ai/free/en/topics/summarization/) · [Text generation (9)](https://md.research.elamur.ai/free/en/topics/text-generation/) · [Code & programming languages (9)](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Legal AI (9)](https://md.research.elamur.ai/free/en/topics/legal-ai/) · [Knowledge graphs & ontologies (8)](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Semantic parsing & meaning representation (8)](https://md.research.elamur.ai/free/en/topics/semantic-parsing/) · [Syntax & grammar formalisms (7)](https://md.research.elamur.ai/free/en/topics/syntax-grammar/) · [Dependency parsing (5)](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [Semantic role labeling (5)](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/) · [Efficient models & compression (5)](https://md.research.elamur.ai/free/en/topics/efficient-models/) · [Speech act theory (3)](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [Treebanks (3)](https://md.research.elamur.ai/free/en/topics/treebanks/) · [Part-of-speech tagging (3)](https://md.research.elamur.ai/free/en/topics/part-of-speech-tagging/) · [Low-resource languages (3)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Interpretability (3)](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Word sense disambiguation (2)](https://md.research.elamur.ai/free/en/topics/word-sense-disambiguation/) · [Tokenization & segmentation (2)](https://md.research.elamur.ai/free/en/topics/tokenization/) · [Grammatical error correction & learner language (2)](https://md.research.elamur.ai/free/en/topics/grammatical-error-correction/) · [Idioms & multiword expressions (2)](https://md.research.elamur.ai/free/en/topics/multiword-expressions/) · [Universal Dependencies (1)](https://md.research.elamur.ai/free/en/topics/universal-dependencies/) · [Morphology (1)](https://md.research.elamur.ai/free/en/topics/morphology/) · [Hebrew & Aramaic (1)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Historical linguistics & language change (1)](https://md.research.elamur.ai/free/en/topics/language-change/)

## Fields

[Natural language processing (269)](https://md.research.elamur.ai/free/en/shelves/nlp/) · [Linguistics & languages (166)](https://md.research.elamur.ai/free/en/shelves/linguistics/) · [Machine translation (46)](https://md.research.elamur.ai/free/en/shelves/machine-translation/) · [Mathematics & statistics (33)](https://md.research.elamur.ai/free/en/shelves/mathematics/) · [AI & machine learning (28)](https://md.research.elamur.ai/free/en/shelves/ai/) · [Law (10)](https://md.research.elamur.ai/free/en/shelves/law/) · [Computing & GPUs (8)](https://md.research.elamur.ai/free/en/shelves/computing/)

## Works by year

20,102,020

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