--- title: "Ming Zhou — papers" description: "Ming Zhou: 21 papers in the Elamur Research library (2014–2022) — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/authors/ming-zhou/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/ming-zhou/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Ming Zhou # Ming Zhou 21 papers on this site (2014–2022) [OpenAlex](https://openalex.org/A5100701572) · [ORCID](https://orcid.org/0000-0002-2551-2964) · h-index 76 · 307 works · 26822 citations (openalex-snapshot, 2026-10-14) Profile data from OpenAlex; authors with the same name are not always told apart. - [BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation](https://md.research.elamur.ai/free/en/papers/jiang-2022-blonde-automatic-evaluation-metric-document/) — Yuchen Jiang, Tianyu Liu, Shuming Ma, et al. · 2022 - [UniXcoder: Unified Cross-Modal Pre-training for Code Representation](https://md.research.elamur.ai/free/en/papers/guo-2022-unixcoder-unified-cross-modal-pre/) — Daya Guo, Shuai Lu, Nan Duan, et al. · 2022 - [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/) — Zhangyin Feng, Daya Guo, Duyu Tang, et al. · 2020 - [InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/) — Zewen Chi, Li Dong, Furu Wei, et al. · 2020 - [K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters](https://md.research.elamur.ai/free/en/papers/wang-2020-k-adapter-infusing-knowledge-pre/) — Ruize Wang, Duyu Tang, Nan Duan, et al. · 2020 - [MIND: A Large-scale Dataset for News Recommendation](https://md.research.elamur.ai/free/en/papers/wu-2020-mind-large-scale-dataset-news/) — Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, et al. · 2020 - [MuTual: A Dataset for Multi-Turn Dialogue Reasoning](https://md.research.elamur.ai/free/en/papers/cui-2020-mutual-dataset-multi-turn-dialogue/) — Leyang Cui, Yu Wu, Shujie Liu, et al. · 2020 - [ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-training](https://md.research.elamur.ai/free/en/papers/qi-2020-prophetnet-predicting-future-n-gram/) — Weizhen Qi, Yu Yan, Yeyun Gong, et al. · 2020 - [Reasoning Over Semantic-Level Graph for Fact Checking](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/) — Wanjun Zhong, Jingjing Xu, Duyu Tang, et al. · 2020 - [UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/) — Hangbo Bao, Li Dong, Furu Wei, et al. · 2020 - [HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization](https://md.research.elamur.ai/free/en/papers/zhang-2019-hibert-document-level-pre-training/) — Xingxing Zhang, Furu Wei, Ming Zhou · 2019 - [LayoutLM: Pre-training of Text and Layout for Document Image Understanding](https://md.research.elamur.ai/free/en/papers/xu-2019-layoutlm-pre-training-text-layout/) — Yiheng Xu, Minghao Li, Lei Cui, et al. · 2019 - [Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks](https://md.research.elamur.ai/free/en/papers/huang-2019-unicoder-universal-language-encoder-pre/) — Haoyang Huang, Yaobo Liang, Nan Duan, et al. · 2019 - [Unified Language Model Pre-training for Natural Language Understanding and Generation](https://md.research.elamur.ai/free/en/papers/dong-2019-unified-language-model-pre-training/) — Li Dong, Nan Yang, Wenhui Wang, et al. · 2019 - [Neural Document Summarization by Jointly Learning to Score and Select Sentences](https://md.research.elamur.ai/free/en/papers/zhou-2018-neural-document-summarization-jointly-learning/) — Qingyu Zhou, Nan Yang, Furu Wei, et al. · 2018 - [Style Transfer as Unsupervised Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2018-style-transfer-unsupervised-machine-translation/) — Zhirui Zhang, Shuo Ren, Shujie Liu, et al. · 2018 - [Gated Self-Matching Networks for Reading Comprehension and Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2017-gated-self-matching-networks-reading/) — Wenhui Wang, Nan Yang, Furu Wei, et al. · 2017 - [Question Generation for Question Answering](https://md.research.elamur.ai/free/en/papers/duan-2017-question-generation-question-answering/) — Nan Duan, Duyu Tang, Peng Chen, et al. · 2017 - [Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-Based Chatbots](https://md.research.elamur.ai/free/en/papers/wu-2017-sequential-matching-network-new-architecture/) — Yu Wu, Wei Wu, Chen Xing, et al. · 2017 - [Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification](https://md.research.elamur.ai/free/en/papers/dong-2014-adaptive-recursive-neural-network-target/) — Li Dong, Furu Wei, Chuanqi Tan, et al. · 2014 - [Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification](https://md.research.elamur.ai/free/en/papers/tang-2014-learning-sentiment-specific-word-embedding/) — Duyu Tang, Furu Wei, Nan Yang, et al. · 2014