---
title: "Microsoft — works of 2020: 32 papers, the most cited first"
description: "32 works of Microsoft from 2020 in our library, the most cited first. Among them: CodeBERT: A Pre-Trained Model for Programming and…"
canonical: "https://research.elamur.ai/free/en/companies/microsoft/year/2020/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/companies/microsoft/year/2020/)

[home](https://md.research.elamur.ai/free/en/) / [institutions](https://md.research.elamur.ai/free/en/orgs/) / [companies](https://md.research.elamur.ai/free/en/companies/) / [Microsoft](https://md.research.elamur.ai/free/en/companies/microsoft/) / 2020

# Works of Microsoft from 2020

32 works · the most cited first · [← Microsoft](https://md.research.elamur.ai/free/en/companies/microsoft/)

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. [**Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing arXiv:2007.15779**Yu Gu; Robert Tinn; Hao Cheng; Michael Lucas; Naoto Usuyama; Xiaodong Liu; Tristan Naumann; Jianfeng Gao;, Hoifung Poon*2020 · 2,655 citations*](https://md.research.elamur.ai/free/en/papers/gu-2020-domain-specific-language-model-pretraining/)
3. **[Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks](https://md.research.elamur.ai/free/en/papers/li-2020-oscar-object-semantics-aligned-pre/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xiujun Li, Xi Yin, Chunyuan Li, et al.*2020 · 1,838 citations*
4. [**DeBERTa: Decoding-enhanced BERT with Disentangled Attention arXiv:2006.03654**Pengcheng He, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 1,808 citations*](https://md.research.elamur.ai/free/en/papers/he-2020-deberta-decoding-enhanced-bert-disentangled/)
5. **[Language (Technology) is Power: A Critical Survey of “Bias” in NLP](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,703 citations*
6. **[The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://md.research.elamur.ai/free/en/papers/joshi-2020-state-fate-linguistic-diversity-inclusion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pratik Joshi, Sebastin Santy, Amar Budhiraja, et al.*2020 · 1,494 citations*
7. [**MPNet: Masked and Permuted Pre-training for Language Understanding arXiv:2004.09297**Kaitao Song, Xu Tan, Tao Qin, et al.*2020 · 948 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-mpnet-masked-permuted-pre-training/)
8. **[RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers](https://md.research.elamur.ai/free/en/papers/wang-2020-rat-sql-relation-aware-schema/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bailin Wang, Richard Shin, Xiaodong Liu, et al.*2020 · 752 citations*
9. **[CORD-19: The COVID-19 Open Research Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-cord-19-covid-19-open/) [Workshop on NLP for COVID-19 at EMNLP](https://md.research.elamur.ai/free/en/venues/nlpcovid19/)**Lucy Lu Wang, Kyle Lo, Yoganand Chandrasekhar, et al.*2020 · 689 citations*
10. [**Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval arXiv:2007.00808**Lee Xiong, Chenyan Xiong, Ye Li, et al.*2020 · 683 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2020-approximate-nearest-neighbor-negative-contrastive/)
11. [**K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters arXiv:2002.01808**Ruize Wang, Duyu Tang, Nan Duan, et al.*2020 · 665 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-k-adapter-infusing-knowledge-pre/)
12. **[MIND: A Large-scale Dataset for News Recommendation](https://md.research.elamur.ai/free/en/papers/wu-2020-mind-large-scale-dataset-news/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, et al.*2020 · 562 citations*
13. **[HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training](https://md.research.elamur.ai/free/en/papers/li-2020-hero-hierarchical-encoder-video-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Linjie Li, Yen-Chun Chen, Yu Cheng, et al.*2020 · 468 citations*
14. **[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/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weizhen Qi, Yu Yan, Yeyun Gong, et al.*2020 · 453 citations*
15. **[Findings of the 2020 Conference on Machine Translation (WMT20)](https://md.research.elamur.ai/free/en/papers/barrault-2020-findings-2020-conference-machine-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Loïc Barrault, Magdalena Biesialska, Ondřej Bojar, et al.*2020 · 401 citations*
16. [**ALFWorld: Aligning Text and Embodied Environments for Interactive Learning arXiv:2010.03768**Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, et al.*2020 · 300 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2020-alfworld-aligning-text-embodied-environments/)
17. **[SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization](https://md.research.elamur.ai/free/en/papers/jiang-2020-smart-robust-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoming Jiang, Pengcheng He, Weizhu Chen, et al.*2020 · 295 citations*
18. **[Fine-grained Fact Verification with Kernel Graph Attention Network](https://md.research.elamur.ai/free/en/papers/liu-2020-fine-grained-fact-verification-kernel/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al.*2020 · 282 citations*
19. **[Text Classification Using Label Names Only: A Language Model Self-Training Approach](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*
20. [**InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training arXiv:2007.07834**Zewen Chi, Li Dong, Furu Wei, et al.*2020 · 271 citations*](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/)
21. **[Few-shot Natural Language Generation for Task-Oriented Dialog](https://md.research.elamur.ai/free/en/papers/peng-2020-few-shot-natural-language-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Baolin Peng, Chenguang Zhu, Chunyuan Li, et al.*2020 · 255 citations*
22. **[Hierarchical Graph Network for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/fang-2020-hierarchical-graph-network-multi-hop/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuwei Fang, Siqi Sun, Zhe Gan, et al.*2020 · 241 citations*
23. **[Understanding the Difficulty of Training Transformers](https://md.research.elamur.ai/free/en/papers/liu-2020-understanding-difficulty-training-transformers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liyuan Liu, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 228 citations*
24. **[GLUECoS: An Evaluation Benchmark for Code-Switched NLP](https://md.research.elamur.ai/free/en/papers/khanuja-2020-gluecos-evaluation-benchmark-code-switched/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Simran Khanuja, Sandipan Dandapat, Anirudh Srinivasan, et al.*2020 · 222 citations*
25. **[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*
26. **[Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space](https://md.research.elamur.ai/free/en/papers/li-2020-optimus-organizing-sentences-pre-trained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chunyuan Li, Xiang Gao, Yuan Li, et al.*2020 · 206 citations*
27. **[Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/zhang-2020-grounded-conversation-generation-as-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Houyu Zhang, Zhenghao Liu, Chenyan Xiong, et al.*2020 · 183 citations*
28. **[Multi-Fact Correction in Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/dong-2020-multi-fact-correction-abstractive-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yue Dong, Shuohang Wang, Zhe Gan, et al.*2020 · 163 citations*
29. [**Generation-Augmented Retrieval for Open-domain Question Answering arXiv:2009.08553**Yuning Mao, Pengcheng He, Xiaodong Liu, et al.*2020 · 150 citations*](https://md.research.elamur.ai/free/en/papers/mao-2020-generation-augmented-retrieval-open-domain/)
30. **[Keep CALM and Explore: Language Models for Action Generation in Text-based Games](https://md.research.elamur.ai/free/en/papers/yao-2020-keep-calm-explore-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shunyu Yao, Rohan Rao, Matthew Hausknecht, et al.*2020 · 127 citations*
31. **[Toward Gender-Inclusive Coreference Resolution](https://md.research.elamur.ai/free/en/papers/cao-2020-gender-inclusive-coreference-resolution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Trista Cao, Hal Daumé III*2020 · 125 citations*
32. **[On the Ability and Limitations of Transformers to Recognize Formal Languages](https://md.research.elamur.ai/free/en/papers/bhattamishra-2020-ability-limitations-transformers-recognize-formal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Satwik Bhattamishra, Kabir Ahuja, Navin Goyal*2020 · 109 citations*
- [← back to](https://md.research.elamur.ai/free/en/companies/microsoft/) — Microsoft
