Tianlin Shi

1.2k total citations · 1 hit paper
8 papers, 514 citations indexed

About

Tianlin Shi is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Tianlin Shi has authored 8 papers receiving a total of 514 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computer Networks and Communications and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Tianlin Shi's work include Sparse and Compressive Sensing Techniques (2 papers), Optimization and Search Problems (2 papers) and Distributed Sensor Networks and Detection Algorithms (2 papers). Tianlin Shi is often cited by papers focused on Sparse and Compressive Sensing Techniques (2 papers), Optimization and Search Problems (2 papers) and Distributed Sensor Networks and Detection Algorithms (2 papers). Tianlin Shi collaborates with scholars based in China and United States. Tianlin Shi's co-authors include Sébastien Jean, Alan Ritter, Dan Jurafsky, Will Monroe, Jiwei Li, Percy Liang, Jun Zhu, Jian Li, Ming Liang and Xiaolin Hu and has published in prestigious journals such as Journal of Machine Learning Research, Operations Research Letters and arXiv (Cornell University).

In The Last Decade

Tianlin Shi

8 papers receiving 487 citations

Hit Papers

1 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.

Adversarial Learning for Neural Dialogue Generation

2017 467 citations Jiwei Li, Will Monroe et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tianlin Shi China	6	399	202	35	30	17	8	514
Junhui Li China	16	642 1.6×	180 0.9×	24 0.7×	51 1.7×	14 0.8×	70	750
Yingming Li China	15	264 0.7×	339 1.7×	49 1.4×	41 1.4×	13 0.8×	55	557
Denis Yarats Israel	8	622 1.6×	353 1.7×	71 2.0×	35 1.2×	23 1.4×	9	778
Chi-Min Chan China	4	254 0.6×	81 0.4×	22 0.6×	43 1.4×	20 1.2×	5	469
Peipei Kang China	10	197 0.5×	141 0.7×	15 0.4×	29 1.0×	30 1.8×	31	368
Baosong Yang China	13	502 1.3×	210 1.0×	33 0.9×	58 1.9×	19 1.1×	41	637
Denny Britz United States	4	354 0.9×	158 0.8×	29 0.8×	37 1.2×	14 0.8×	4	451
Weize Chen China	3	226 0.6×	67 0.3×	25 0.7×	45 1.5×	21 1.2×	5	440
Pengda Qin China	9	370 0.9×	94 0.5×	17 0.5×	41 1.4×	10 0.6×	14	455
Fangxiang Feng China	14	615 1.5×	628 3.1×	29 0.8×	56 1.9×	20 1.2×	38	1.1k

Countries citing papers authored by Tianlin Shi

Since Specialization

Citations

This map shows the geographic impact of Tianlin Shi'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 Tianlin Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianlin Shi more than expected).

Fields of papers citing papers by Tianlin Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tianlin Shi. 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 Tianlin Shi. The network helps show where Tianlin Shi may publish in the future.

Co-authorship network of co-authors of Tianlin Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Tianlin Shi. A scholar is included among the top collaborators of Tianlin Shi 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 Tianlin Shi. Tianlin Shi 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:

8 of 8 papers shown

1.

Shi, Tianlin, et al.. (2017). World of Bits: An Open-Domain Platform for Web-Based Agents. International Conference on Machine Learning. 3135–3144. 11 indexed citations

2.

Li, Jiwei, Will Monroe, Tianlin Shi, et al.. (2017). Adversarial Learning for Neural Dialogue Generation. 2157–2169. 467 indexed citations breakdown →

3.

Shi, Tianlin, et al.. (2016). Improving Survey Aggregation with Sparsely Represented Signals. 1845–1854. 2 indexed citations

4.

Shi, Tianlin, Jacob Steinhardt, & Percy Liang. (2015). Learning Where to Sample in Structured Prediction. International Conference on Artificial Intelligence and Statistics. 875–884. 7 indexed citations

5.

Li, Jian & Tianlin Shi. (2014). A fully polynomial-time approximation scheme for approximating a sum of random variables. Operations Research Letters. 42(3). 197–202. 6 indexed citations

6.

Shi, Tianlin, Ming Liang, & Xiaolin Hu. (2014). A Reverse Hierarchy Model for Predicting Eye Fixations. arXiv (Cornell University). 34. 2822–2829. 9 indexed citations

7.

Shi, Tianlin, Da Tang, Liwen Xu, & Thomas Moscibroda. (2014). Correlated compressive sensing for networked data. 722–731. 4 indexed citations

8.

Shi, Tianlin & Jun Zhu. (2013). Online Bayesian Passive-Aggressive Learning. Journal of Machine Learning Research. 18(1). 1084–1122. 8 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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