---
title: "China — works"
description: "Works of China: 616 in our library · page 1 of 7, the most cited first."
canonical: "https://research.elamur.ai/free/en/countries/china/works/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/countries/china/works/)

[home](https://md.research.elamur.ai/free/en/) / [countries](https://md.research.elamur.ai/free/en/countries/) / [China](https://md.research.elamur.ai/free/en/countries/china/) / works

# Works of China

616 · page 1 of 7 · the most cited first · [← China](https://md.research.elamur.ai/free/en/countries/china/)

**1** [2](https://md.research.elamur.ai/free/en/countries/china/works/page/2/) … [7](https://md.research.elamur.ai/free/en/countries/china/works/page/7/) [next →](https://md.research.elamur.ai/free/en/countries/china/works/page/2/)

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/)
26. [**Parameter-efficient fine-tuning of large-scale pre-trained language models**Ning Ding, Yujia Qin, Guang You Yang, et al.*2023 · 1,324 citations*](https://md.research.elamur.ai/free/en/papers/ding-2023-parameter-efficient-fine-tuning-large/)
27. [**The Rise and Potential of Large Language Model Based Agents: A Survey**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,262 citations*](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/)
28. [**Neural Responding Machine for Short-Text Conversation**Lifeng Shang, Zhengdong Lu, Hang Li*2015 · 1,242 citations*](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/)
29. [**Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification**Li Dong, Furu Wei, Chuanqi Tan, et al.*2014 · 1,211 citations*](https://md.research.elamur.ai/free/en/papers/dong-2014-adaptive-recursive-neural-network-target/)
30. [**M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation**Jianlv Chen, Shitao Xiao, Peitian Zhang, et al.*2024 · 1,196 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-m3-embedding-multi-linguality/)
31. [**Opinion Word Expansion and Target Extraction through Double Propagation**Guang Qiu, Bing Liu, Jiajun Bu, et al.*2011 · 1,196 citations*](https://md.research.elamur.ai/free/en/papers/qiu-2011-opinion-word-expansion-target-extraction/)
32. [**Aspect Level Sentiment Classification with Deep Memory Network**Duyu Tang, Bing Qin, Ting Liu*2016 · 1,187 citations*](https://md.research.elamur.ai/free/en/papers/tang-2016-aspect-level-sentiment-classification-deep/)
33. [**Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks**Yubo Chen, Liheng Xu, Kang Liu, et al.*2015 · 1,170 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-event-extraction-dynamic-multi-pooling/)
34. [**Recurrent Attention Network on Memory for Aspect Sentiment Analysis**Peng Chen, Zhongqian Sun, Lidong Bing, et al.*2017 · 1,113 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-recurrent-attention-network-memory-aspect/)
35. [**A Survey on Multimodal Large Language Models**Shukang Yin, Chaoyou Fu, Sirui Zhao, et al.*2023 · 1,060 citations*](https://md.research.elamur.ai/free/en/papers/yin-2023-survey-multimodal-large-language-models/)
36. [**GPT Understands, Too**Xiao Liu, Yanan Zheng, Zhengxiao Du, et al.*2021 · 1,039 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-gpt-understands-too/)
37. [**LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,035 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/)
38. [**P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks**Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.*2022 · 1,013 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-p-tuning-prompt-tuning-can/)
39. [**VL-BERT: Pre-training of Generic Visual-Linguistic Representations**Weijie Su, Xizhou Zhu, Yue Cao, et al.*2019 · 1,008 citations*](https://md.research.elamur.ai/free/en/papers/su-2019-vl-bert-pre-training-generic/)
40. [**A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models**Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li*2024 · 1,006 citations*](https://md.research.elamur.ai/free/en/papers/fan-2024-survey-rag-meeting-llms-towards/)
41. [**K-BERT: Enabling Language Representation with Knowledge Graph**Weijie Liu, Peng Zhou, Zhe Zhao, et al.*2019 · 1,006 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/)
42. [**Evaluating Object Hallucination in Large Vision-Language Models**Yifan Li, Yifan Du, Kun Zhou, et al.*2023 · 986 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/)
43. [**ERNIE 2.0: A Continual Pre-training Framework for Language Understanding**Yu Sun, Shuohuan Wang, Yukun Li, et al.*2019 · 976 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-2-0-continual/)
44. [**Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 962 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/)
45. [**ERNIE: Enhanced Representation through Knowledge Integration**Yu Sun, Shuohuan Wang, Yukun Li, et al.*2019 · 949 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-enhanced-representation-through-knowledge/)
46. [**MPNet: Masked and Permuted Pre-training for Language Understanding**Kaitao Song, Xu Tan, Tao Qin, et al.*2020 · 944 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-mpnet-masked-permuted-pre-training/)
47. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 936 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/)
48. [**Modeling Coverage for Neural Machine Translation**Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al.*2016 · 927 citations*](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/)
49. [**C-Pack: Packed Resources For General Chinese Embeddings**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 920 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/)
50. [**Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond**Jinze Bai, Shuai Bai, Shusheng Yang, et al.*2023 · 913 citations*](https://md.research.elamur.ai/free/en/papers/bai-2023-qwen-vl-versatile-vision-language/)
51. [**Learning to Ask: Neural Question Generation for Reading Comprehension**Xinya Du, Junru Shao, Claire Cardie*2017 · 913 citations*](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/)
52. [**MMBench: Is Your Multi-modal Model an All-around Player?**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 907 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/)
53. [**Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme**Suncong Zheng, Feng Wang, Hongyun Bao, et al.*2017 · 902 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2017-joint-extraction-entities-relations-based/)
54. [**LayoutLM: Pre-training of Text and Layout for Document Image Understanding**Yiheng Xu, Minghao Li, Lei Cui, et al.*2019 · 889 citations*](https://md.research.elamur.ai/free/en/papers/xu-2019-layoutlm-pre-training-text-layout/)
55. [**Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency**Shuhuai Ren, Yihe Deng, Kun He, et al.*2019 · 884 citations*](https://md.research.elamur.ai/free/en/papers/ren-2019-generating-natural-language-adversarial-examples/)
56. [**BERT-ATTACK: Adversarial Attack Against BERT Using BERT**Linyang Li, Ruotian Ma, Qipeng Guo, et al.*2020 · 840 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-bert-attack-adversarial-attack-against/)
57. [**A Unified MRC Framework for Named Entity Recognition**Xiaoya Li, Jingrong Feng, Yuxian Meng, et al.*2020 · 833 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-unified-mrc-framework-named-entity/)
58. [**Gated Self-Matching Networks for Reading Comprehension and Question Answering**Wenhui Wang, Nan Yang, Furu Wei, et al.*2017 · 823 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-gated-self-matching-networks-reading/)
59. [**Is ChatGPT a General-Purpose Natural Language Processing Task Solver?**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 818 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)
60. [**Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks**Chen Zhang, Qiuchi Li, Dawei Song*2019 · 807 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-aspect-based-sentiment-classification-aspect/)
61. [**Learning Deep Transformer Models for Machine Translation**Qiang Wang, Bei Li, Tong Xiao, et al.*2019 · 798 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-learning-deep-transformer-models-machine/)
62. [**Multi-Task Learning for Multiple Language Translation**Daxiang Dong, Hua Wu, Wei He, et al.*2015 · 791 citations*](https://md.research.elamur.ai/free/en/papers/dong-2015-multi-task-learning-multiple-language/)
63. [**Revisiting Pre-Trained Models for Chinese Natural Language Processing**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2020 · 788 citations*](https://md.research.elamur.ai/free/en/papers/cui-2020-revisiting-pre-trained-models-chinese/)
64. [**Explainability for Large Language Models: A Survey**Haiyan Zhao, Hanjie Chen, Fan Yang, et al.*2023 · 785 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-explainability-large-language-models-survey/)
65. [**Relational Graph Attention Network for Aspect-based Sentiment Analysis**Kai Wang, Weizhou Shen, Yunyi Yang, et al.*2020 · 775 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-relational-graph-attention-network-aspect/)
66. [**GLM-130B: An Open Bilingual Pre-trained Model**Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.*2022 · 775 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-glm-130b-open-bilingual-pre/)
67. [**LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking**Yupan Huang, Tengchao Lv, Lei Cui, et al.*2022 · 774 citations*](https://md.research.elamur.ai/free/en/papers/huang-2022-layoutlmv3-pre-training-document-ai/)
68. [**Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths**Yan Xu, Lili Mou, Ge Li, et al.*2015 · 769 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-classifying-relations-long-short-term/)
69. [**UniXcoder: Unified Cross-Modal Pre-training for Code Representation**Daya Guo, Shuai Lu, Nan Duan, et al.*2022 · 768 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-unixcoder-unified-cross-modal-pre/)
70. [**Dice Loss for Data-imbalanced NLP Tasks**Xiaoya Li, Xiaofei Sun, Yuxian Meng, et al.*2020 · 734 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-dice-loss-data-imbalanced-nlp/)
71. [**A Novel Cascade Binary Tagging Framework for Relational Triple Extraction**Zhepei Wei, Jianlin Su, Yue Wang, et al.*2020 · 732 citations*](https://md.research.elamur.ai/free/en/papers/wei-2020-novel-cascade-binary-tagging-framework/)
72. [**WizardLM: Empowering large pre-trained language models to follow complex instructions**Can Xu, Qingfeng Sun, Kai Zheng, et al.*2023 · 729 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-wizardlm-empowering-large-pre-trained/)
73. [**Adversarial Multi-task Learning for Text Classification**Pengfei Liu, Xipeng Qiu, Xuanjing Huang*2017 · 723 citations*](https://md.research.elamur.ai/free/en/papers/liu-2017-adversarial-multi-task-learning-text/)
74. [**Style Transfer in Text: Exploration and Evaluation**Zhenxin Fu, Xiaoye Tan, Nanyun Peng, et al.*2017 · 701 citations*](https://md.research.elamur.ai/free/en/papers/fu-2017-style-transfer-text-exploration-evaluation/)
75. [**Modeling Relation Paths for Representation Learning of Knowledge Bases**Yankai Lin, Zhiyuan Liu, Huanbo Luan, et al.*2015 · 695 citations*](https://md.research.elamur.ai/free/en/papers/lin-2015-modeling-relation-paths-representation-learning/)
76. [**Effective LSTMs for Target-Dependent Sentiment Classification**Duyu Tang, Bing Qin, Xiaocheng Feng, et al.*2016 · 693 citations*](https://md.research.elamur.ai/free/en/papers/tang-2016-effective-lstms-target-dependent-sentiment/)
77. [**ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools**Team GLM, Aohan Zeng, Bin Xu, et al.*2024 · 687 citations*](https://md.research.elamur.ai/free/en/papers/glm-2024-chatglm-family-large-language-models/)
78. [**K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters**Ruize Wang, Duyu Tang, Nan Duan, et al.*2020 · 662 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-k-adapter-infusing-knowledge-pre/)
79. [**ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer**Yuanmeng Yan, Rumei Li, Sirui Wang, et al.*2021 · 647 citations*](https://md.research.elamur.ai/free/en/papers/yan-2021-consert-contrastive-framework-self-supervised/)
80. [**HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models**Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, et al.*2023 · 646 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-halueval-large-scale-hallucination-evaluation/)
81. [**Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate**Tian Liang, Zhiwei He, Wenxiang Jiao, et al.*2023 · 643 citations*](https://md.research.elamur.ai/free/en/papers/liang-2023-encouraging-divergent-thinking-large-language/)
82. [**ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge**Yunxiang Li, Zihan Li, Kai Zhang, et al.*2023 · 640 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-chatdoctor-medical-chat-model-fine/)
83. [**Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine**Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, et al.*2023 · 626 citations*](https://md.research.elamur.ai/free/en/papers/jiao-2023-chatgpt-good-translator-yes-gpt/)
84. [**Benchmarking Large Language Models in Retrieval-Augmented Generation**Jiawei Chen, Hongyu Lin, Xianpei Han, et al.*2023 · 624 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-benchmarking-large-language-models-retrieval/)
85. [**Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-Based Chatbots**Yu Wu, Wei Wu, Chen Xing, et al.*2017 · 624 citations*](https://md.research.elamur.ai/free/en/papers/wu-2017-sequential-matching-network-new-architecture/)
86. [**LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding**Yang Xu, Yiheng Xu, Tengchao Lv, et al.*2021 · 623 citations*](https://md.research.elamur.ai/free/en/papers/xu-2021-layoutlmv2-multi-modal-pre-training/)
87. [**Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm**Bjarke Felbo, Alan Mislove, Anders Søgaard, et al.*2017 · 617 citations*](https://md.research.elamur.ai/free/en/papers/felbo-2017-millions-emoji-occurrences-learn-any/)
88. [**Video-LLaVA: Learning United Visual Representation by Alignment Before Projection**Bin Lin, Yang Ye, Bin Zhu, et al.*2023 · 614 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-video-llava-learning-united-visual/)
89. [**Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism**Xiangrong Zeng, Daojian Zeng, Shizhu He, et al.*2018 · 607 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2018-extracting-relational-facts-end-end/)
90. [**RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering**Yingqi Qu, Yuchen Ding, Jing Liu, et al.*2021 · 601 citations*](https://md.research.elamur.ai/free/en/papers/qu-2021-rocketqa-optimized-training-approach-dense/)
91. [**A Joint Neural Model for Information Extraction with Global Features**Ying Lin, Heng Ji, Fei Huang, et al.*2020 · 600 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-joint-neural-model-information-extraction/)
92. [**HybridFlow: A Flexible and Efficient RLHF Framework**Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.*2024 · 598 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2024-hybridflow-flexible-efficient-rlhf-framework/)
93. [**Transformation Networks for Target-Oriented Sentiment Classification**Xin Li, Lidong Bing, Wai Lam, et al.*2018 · 594 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-transformation-networks-target-oriented-sentiment/)
94. [**Co-Training for Cross-Lingual Sentiment Classification**Xiaojun Wan*2009 · 594 citations*](https://md.research.elamur.ai/free/en/papers/wan-2009-co-training-cross-lingual-sentiment/)
95. [**A Robustly Optimized BERT Pre-training Approach with Post-training**Liu Zhuang, Lin Wayne, Shi Ya, et al.*2021 · 585 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2021-robustly-optimized-bert-pre-training/)
96. [**AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation**Qingyun Wu, Gagan Bansal, Jieyu Zhang, et al.*2023 · 584 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-autogen-enabling-next-gen-llm/)
97. [**QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension**Adams Wei Yu, David Dohan, Minh-Thang Luong, et al.*2018 · 581 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-qanet-combining-local-convolution-global/)
98. [**Relation Classification via Multi-Level Attention CNNs**Linlin Wang, Zhu Cao, Gerard de Melo, et al.*2016 · 573 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-relation-classification-multi-level-attention/)
99. [**Minimum Risk Training for Neural Machine Translation**Shiqi Shen, Yong Cheng, Zhongjun He, et al.*2015 · 572 citations*](https://md.research.elamur.ai/free/en/papers/shen-2015-minimum-risk-training-neural-machine/)
100. [**Extractive Summarization as Text Matching**Ming Zhong, Pengfei Liu, Yiran Chen, et al.*2020 · 567 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2020-extractive-summarization-as-text-matching/)

**1** [2](https://md.research.elamur.ai/free/en/countries/china/works/page/2/) … [7](https://md.research.elamur.ai/free/en/countries/china/works/page/7/) [next →](https://md.research.elamur.ai/free/en/countries/china/works/page/2/)

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