John X. Morris

855 total citations · 1 hit paper
11 papers, 394 citations indexed

About

John X. Morris is a scholar working on Artificial Intelligence, Signal Processing and Communication. According to data from OpenAlex, John X. Morris has authored 11 papers receiving a total of 394 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 2 papers in Signal Processing and 1 paper in Communication. Recurrent topics in John X. Morris's work include Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers) and Adversarial Robustness in Machine Learning (3 papers). John X. Morris is often cited by papers focused on Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers) and Adversarial Robustness in Machine Learning (3 papers). John X. Morris collaborates with scholars based in United States, United Kingdom and India. John X. Morris's co-authors include Yanjun Qi, Jin Yong Yoo, Eli Lifland, Jake Grigsby, Di Jin, Alexander M. Rush, Vitaly Shmatikov, Volodymyr Kuleshov, Chandan Singh and Jianfeng Gao and has published in prestigious journals such as Isis, arXiv (Cornell University) and Computers and the Humanities.

In The Last Decade

John X. Morris

11 papers receiving 378 citations

Hit Papers

TextAttack: A Framework for Adversarial Attacks, Data Aug... 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John X. Morris United States 5 342 86 48 46 33 11 394
Jin Yong Yoo United States 5 324 0.9× 82 1.0× 47 1.0× 40 0.9× 34 1.0× 6 364
Eli Lifland United States 4 326 1.0× 83 1.0× 48 1.0× 38 0.8× 31 0.9× 4 374
Jake Grigsby United States 2 268 0.8× 66 0.8× 37 0.8× 33 0.7× 26 0.8× 2 313
Ahoud Alhazmi Australia 4 248 0.7× 68 0.8× 48 1.0× 42 0.9× 21 0.6× 8 293
Shuhuai Ren China 8 404 1.2× 106 1.2× 52 1.1× 99 2.2× 34 1.0× 14 477
Yihe Deng China 2 390 1.1× 115 1.3× 47 1.0× 42 0.9× 32 1.0× 4 409
Dingfan Chen Germany 5 271 0.8× 40 0.5× 33 0.7× 73 1.6× 12 0.4× 9 311
Roman Englert Germany 8 176 0.5× 107 1.2× 38 0.8× 46 1.0× 19 0.6× 23 262
Sahar Abdelnabi Germany 4 148 0.4× 55 0.6× 55 1.1× 94 2.0× 39 1.2× 11 289
Meng Zhao China 8 318 0.9× 23 0.3× 45 0.9× 61 1.3× 11 0.3× 34 380

Countries citing papers authored by John X. Morris

Since Specialization
Citations

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

Fields of papers citing papers by John X. Morris

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John X. Morris. 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 John X. Morris. The network helps show where John X. Morris may publish in the future.

Co-authorship network of co-authors of John X. Morris

This figure shows the co-authorship network connecting the top 25 collaborators of John X. Morris. A scholar is included among the top collaborators of John X. Morris 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 John X. Morris. John X. Morris is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Morris, John X., et al.. (2024). Extracting Prompts by Inverting LLM Outputs. 14753–14777. 4 indexed citations
2.
Singh, Chandan, John X. Morris, Jyoti Aneja, Alexander M. Rush, & Jianfeng Gao. (2023). Explaining Data Patterns in Natural Language with Language Models. 31–55. 6 indexed citations
3.
Morris, John X., Volodymyr Kuleshov, Vitaly Shmatikov, & Alexander M. Rush. (2023). Text Embeddings Reveal (Almost) As Much As Text. 12448–12460. 19 indexed citations
4.
Singh, Chandan, John X. Morris, Alexander M. Rush, Jianfeng Gao, & Yuntian Deng. (2023). Tree Prompting: Efficient Task Adaptation without Fine-Tuning. 6253–6267. 2 indexed citations
5.
Morris, John X., Justin Chiu, Ramin Zabih, & Alexander M. Rush. (2022). Unsupervised Text Deidentification. 4777–4788. 3 indexed citations
6.
Morris, John X., Eli Lifland, Jin Yong Yoo, & Yanjun Qi. (2020). TextAttack: A Framework for Adversarial Attacks in Natural Language Processing. arXiv (Cornell University). 24 indexed citations
7.
Morris, John X., Eli Lifland, Jin Yong Yoo, et al.. (2020). TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP. 119–126. 302 indexed citations breakdown →
8.
Morris, John X., Jin Yong Yoo, & Yanjun Qi. (2020). TextAttack: Lessons learned in designing Python frameworks for NLP. 126–131. 4 indexed citations
9.
Yoo, Jin Yong, John X. Morris, Eli Lifland, & Yanjun Qi. (2020). Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples. 323–332. 24 indexed citations
10.
Morris, John X.. (1969). Pattern Recognition in Descartes' Automata. Isis. 60(4). 451–460. 4 indexed citations
11.
Morris, John X.. (1969). A computer-assisted study of a philosophical text. Computers and the Humanities. 3(3). 175–178. 2 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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