Eli Lifland

777 citations
4 papers · 374 indexed · 1 hit paper · h-index 4
Topics
Topic Modeling (3 papers)Adversarial Robustness in Machine Learning (3 papers)Advanced Malware Detection Techniques (2 papers)
Journals
IEEE Internet of Things JournalarXiv (Cornell University)
Partner nations
United StatesAustria

In The Last Decade

Eli Lifland

4 papers receiving 360 citations

Hit Papers

TextAttack: A Framework for Adversarial Attacks, Data Aug...20202026202220242020100200300

Peers

Eli Lifland
Comparison fields: 5 of 53
  • Artificial Intelligence 326
  • Signal Processing 83
  • Information Systems 48
  • Computer Vision and Pattern Recognition 38
  • Computer Networks and Communications 34
Replace Jin Yong Yoo with:
Jin Yong Yoo United States
John X. Morris United States
Ahmed Salem China
Ahoud Alhazmi Australia
Fanchao Qi China
Shruti Tople United Kingdom
Qingni Shen China
Christopher A. Choquette-Choo United States
Sahar Abdelnabi Germany
Jiazhu Dai China
Eli Lifland relative to Jin Yong Yoo United States Jin Yong Yoo's profile →
Citations per field
00.5×1.5×
Jin Yong Yoo · 1×
Citations per year

Countries citing papers authored by Eli Lifland

Since Specialization
Citations

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

Fields of papers citing papers by Eli Lifland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eli Lifland

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

All Works

4 of 4 papers shown
#WorkIndexed citations
1 24
2
TextAttack: A Framework for Adversarial Attacks in Natural Language Processing
24
3
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLPbreakdown →
302
4 24

About Eli Lifland

Eli Lifland is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 4 papers that have together received 374 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Adversarial Robustness in Machine Learning (3 papers) and Advanced Malware Detection Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (326 citations), Signal Processing (83 citations) and Health Informatics (5 citations). Eli Lifland has collaborated with scholars based in United States and Austria. Frequent co-authors include John X. Morris, Yanjun Qi, Jin Yong Yoo, Jake Grigsby, Di Jin, Ezio Bartocci, Lu Feng, John A. Stankovic and Meiyi Ma. Their work appears in journals such as IEEE Internet of Things Journal and arXiv (Cornell University).

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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