Shuo Ren

3.2k total citations · 2 hit papers
14 papers, 1.4k citations indexed

About

Shuo Ren is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Shuo Ren has authored 14 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Shuo Ren's work include Natural Language Processing Techniques (12 papers), Topic Modeling (12 papers) and Speech Recognition and Synthesis (6 papers). Shuo Ren is often cited by papers focused on Natural Language Processing Techniques (12 papers), Topic Modeling (12 papers) and Speech Recognition and Synthesis (6 papers). Shuo Ren collaborates with scholars based in China, United States and United Kingdom. Shuo Ren's co-authors include Shujie Liu, Long Zhou, Yu Wu, Jinyu Li, Chengyi Wang, Furu Wei, Yao Qian, Yanmin Qian, Michael Zeng and Sanyuan Chen and has published in prestigious journals such as IEEE Journal of Selected Topics in Signal Processing, IEEE/ACM Transactions on Audio Speech and Language Processing and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

In The Last Decade

Shuo Ren

14 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

2022 832 citations Sanyuan Chen, Chengyi Wang et al. IEEE Journal of Selected Topics in Signal Processing profile →
GraphCodeBERT: Pre-training Code Representations with Data Flow

2021 261 citations Daya Guo, Shuo Ren et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Shuo Ren China	11	1.0k	638	221	169	127	14	1.4k
Alexei Baevski Israel	15	2.4k 2.3×	572 0.9×	97 0.4×	654 3.9×	80 0.6×	26	2.7k
Ananya Misra United States	12	416 0.4×	439 0.7×	134 0.6×	91 0.5×	16 0.1×	34	876
Roland Kühn Canada	21	2.0k 1.9×	596 0.9×	108 0.5×	244 1.4×	46 0.4×	75	2.1k
Changhan Wang United States	18	1.1k 1.0×	280 0.4×	42 0.2×	161 1.0×	35 0.3×	41	1.2k
Ian McGraw United States	14	777 0.7×	388 0.6×	49 0.2×	93 0.6×	32 0.3×	33	966
Spyros Matsoukas United States	23	1.4k 1.4×	647 1.0×	66 0.3×	174 1.0×	46 0.4×	76	1.6k
Artur Janicki Poland	11	313 0.3×	258 0.4×	63 0.3×	142 0.8×	39 0.3×	49	482
Timothy J. Hazen United States	26	2.0k 1.9×	1.3k 2.0×	117 0.5×	312 1.8×	88 0.7×	72	2.4k
Kadri Hacıoğlu United States	19	1.4k 1.4×	154 0.2×	121 0.5×	101 0.6×	39 0.3×	56	1.7k
M. Weintraub United States	17	1.2k 1.1×	827 1.3×	37 0.2×	125 0.7×	179 1.4×	43	1.3k

Countries citing papers authored by Shuo Ren

Since Specialization

Citations

This map shows the geographic impact of Shuo Ren's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shuo Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuo Ren more than expected).

Fields of papers citing papers by Shuo Ren

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shuo Ren. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shuo Ren. The network helps show where Shuo Ren may publish in the future.

Co-authorship network of co-authors of Shuo Ren

This figure shows the co-authorship network connecting the top 25 collaborators of Shuo Ren. A scholar is included among the top collaborators of Shuo Ren based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shuo Ren. Shuo Ren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

1.

Zhang, Ziqiang, Sanyuan Chen, Long Zhou, et al.. (2024). SpeechLM: Enhanced Speech Pre-Training With Unpaired Textual Data. IEEE/ACM Transactions on Audio Speech and Language Processing. 32. 2177–2187. 16 indexed citations

2.

Wang, Rui, Long Zhou, Chengyi Wang, et al.. (2022). SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 5723–5738. 70 indexed citations

3.

Ren, Shuo, Yao Qian, Shujie Liu, et al.. (2022). Optimizing Alignment of Speech and Language Latent Spaces for End-To-End Speech Recognition and Understanding. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7802–7806. 10 indexed citations

4.

Chen, Sanyuan, Chengyi Wang, Zhengyang Chen, et al.. (2022). WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing. IEEE Journal of Selected Topics in Signal Processing. 16(6). 1505–1518. 832 indexed citations breakdown →

5.

Ren, Shuo, Long Zhou, Shujie Liu, et al.. (2021). SemFace: Pre-training Encoder and Decoder with a Semantic Interface for Neural Machine Translation. 4518–4527. 8 indexed citations

6.

Guo, Daya, Shuo Ren, Shuai Lu, et al.. (2021). GraphCodeBERT: Pre-training Code Representations with Data Flow. 261 indexed citations breakdown →

7.

Wang, Chengyi, Yu Wu, Jinyu Li, et al.. (2020). Semantic Mask for Transformer Based End-to-End Speech Recognition. 971–975. 31 indexed citations

8.

Ren, Shuo, Yu Wu, Shujie Liu, Ming Zhou, & Shuai Ma. (2020). A Retrieve-and-Rewrite Initialization Method for Unsupervised Machine Translation. 11 indexed citations

9.

Ren, Shuo, Shujie Liu, Ming Zhou, & Shuai Ma. (2020). A Graph-based Coarse-to-fine Method for Unsupervised Bilingual Lexicon Induction. 3476–3485. 7 indexed citations

10.

Ren, Shuo, Yu Wu, Shujie Liu, Ming Zhou, & Shuai Ma. (2019). Explicit Cross-lingual Pre-training for Unsupervised Machine Translation. 770–779. 17 indexed citations

11.

Ren, Shuo, Zhirui Zhang, Shujie Liu, Ming Zhou, & Shuai Ma. (2019). Unsupervised Neural Machine Translation with SMT as Posterior Regularization. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 241–248. 40 indexed citations

12.

Ren, Shuo, Wenhu Chen, Shujie Liu, et al.. (2018). Triangular Architecture for Rare Language Translation. 56–65. 16 indexed citations

13.

Chen, Wenhu, Shuo Ren, Shujie Liu, et al.. (2018). Generative Bridging Network for Neural Sequence Prediction. 1706–1715. 2 indexed citations

14.

Chen, Shi, Shujie Liu, Shuo Ren, et al.. (2016). Knowledge-Based Semantic Embedding for Machine Translation. 2245–2254. 35 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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