Leonid Karlinsky

3.2k total citations
45 papers, 1.0k citations indexed

About

Leonid Karlinsky is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Leonid Karlinsky has authored 45 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 25 papers in Computer Vision and Pattern Recognition and 5 papers in Signal Processing. Recurrent topics in Leonid Karlinsky's work include Domain Adaptation and Few-Shot Learning (19 papers), Multimodal Machine Learning Applications (16 papers) and Advanced Image and Video Retrieval Techniques (9 papers). Leonid Karlinsky is often cited by papers focused on Domain Adaptation and Few-Shot Learning (19 papers), Multimodal Machine Learning Applications (16 papers) and Advanced Image and Video Retrieval Techniques (9 papers). Leonid Karlinsky collaborates with scholars based in United States, Israel and Japan. Leonid Karlinsky's co-authors include Rogério Feris, Raja Giryes, Joseph Shtok, Sivan Harary, Eli Schwartz, Alex Bronstein, Amit Aides, Rameswar Panda, Tomer Michaeli and Assaf Arbelle and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition Letters and Computer Vision and Image Understanding.

In The Last Decade

Leonid Karlinsky

41 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Leonid Karlinsky United States	17	665	658	132	83	49	45	1.0k
Qiu Chen Japan	16	316 0.5×	436 0.7×	55 0.4×	81 1.0×	27 0.6×	97	821
Alaaeldin El-Nouby Sweden	4	352 0.5×	438 0.7×	79 0.6×	52 0.6×	75 1.5×	6	835
Chenxi Liu United States	6	412 0.6×	693 1.1×	81 0.6×	92 1.1×	25 0.5×	12	916
David Dohan United States	5	548 0.8×	700 1.1×	132 1.0×	71 0.9×	30 0.6×	10	1.0k
Siti Noraini Sulaiman Malaysia	15	369 0.6×	379 0.6×	137 1.0×	137 1.7×	20 0.4×	106	932
Zhao-Min Chen China	5	587 0.9×	578 0.9×	66 0.5×	64 0.8×	41 0.8×	7	948
Sachin Ravi United States	5	1.0k 1.6×	706 1.1×	147 1.1×	51 0.6×	51 1.0×	5	1.2k
Yogesh Balaji United States	10	772 1.2×	879 1.3×	169 1.3×	65 0.8×	39 0.8×	13	1.2k
Hui Tang China	12	654 1.0×	595 0.9×	138 1.0×	38 0.5×	35 0.7×	40	1.1k
Wonmin Byeon United States	11	322 0.5×	652 1.0×	82 0.6×	47 0.6×	44 0.9×	22	963

Countries citing papers authored by Leonid Karlinsky

Since Specialization

Citations

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

Fields of papers citing papers by Leonid Karlinsky

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonid Karlinsky

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

All Works

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20 of 20 papers shown

Naparstek, Oshri, et al.. (2025). REAL-MM-RAG: A Real-World Multi-Modal Retrieval Benchmark. 31660–31683.

Smith, James, et al.. (2024). Adaptive Memory Replay for Continual Learning. 3605–3615. 4 indexed citations

Schwartz, Eli, et al.. (2024). NumeroLogic: Number Encoding for Enhanced LLMs’ Numerical Reasoning. 206–212. 2 indexed citations

Herzig, Roei, Leonid Karlinsky, Assaf Arbelle, et al.. (2023). Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs. 14077–14098. 6 indexed citations

Karlinsky, Leonid, et al.. (2023). Computer Vision – ECCV 2022 Workshops. Lecture notes in computer science. 6 indexed citations

Gong, Yuan, Sameer Khurana, Leonid Karlinsky, & James Glass. (2023). Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers. 2798–2802. 23 indexed citations

Karlinsky, Leonid, et al.. (2023). Computer Vision – ECCV 2022 Workshops. Lecture notes in computer science.

Karlinsky, Leonid, et al.. (2023). Computer Vision – ECCV 2022 Workshops. Lecture notes in computer science. 31 indexed citations

Karlinsky, Leonid, et al.. (2023). Computer Vision – ECCV 2022 Workshops. Lecture notes in computer science. 8 indexed citations

10.

Karlinsky, Leonid, et al.. (2023). Computer Vision – ECCV 2022 Workshops. Lecture notes in computer science. 13 indexed citations

11.

Liu, Alexander H., et al.. (2023). Joint Audio and Speech Understanding. 1–8. 13 indexed citations

12.

Arbelle, Assaf, Sivan Harary, Eli Schwartz, et al.. (2023). Teaching Structured Vision & Language Concepts to Vision & Language Models. 2657–2668. 19 indexed citations

13.

Smith, James, Paola Cascante-Bonilla, Assaf Arbelle, et al.. (2023). ConStruct-VL: Data-Free Continual Structured VL Concepts Learning*. 14994–15004. 7 indexed citations

14.

Lee, Joshua, Prasanna Sattigeri, Rameswar Panda, et al.. (2022). A Maximal Correlation Framework for Fair Machine Learning. Entropy. 24(4). 461–461. 2 indexed citations

15.

Schwartz, Eli, Leonid Karlinsky, Rogério Feris, Raja Giryes, & Alex Bronstein. (2022). Baby steps towards few-shot learning with multiple semantics. Pattern Recognition Letters. 160. 142–147. 39 indexed citations

16.

Guo, Yunhui, Noel Codella, Leonid Karlinsky, et al.. (2019). A New Benchmark for Evaluation of Cross-Domain Few-Shot Learning.. arXiv (Cornell University). 20 indexed citations

17.

Karlinsky, Leonid, Amit Aides, Joseph Shtok, et al.. (2019). LaSO: Label-Set Operations Networks for Multi-Label Few-Shot Learning. 6541–6550. 78 indexed citations

18.

Schwartz, Eli, Leonid Karlinsky, Joseph Shtok, et al.. (2018). Delta-encoder: an effective sample synthesis method for few-shot object recognition. arXiv (Cornell University). 31. 2845–2855. 64 indexed citations

19.

Kumar, Abhishek, Prasanna Sattigeri, Leonid Karlinsky, et al.. (2018). Co-regularized Alignment for Unsupervised Domain Adaptation. arXiv (Cornell University). 31. 9345–9356. 49 indexed citations

20.

Karlinsky, Leonid, Michael Dinerstein, & Shimon Ullman. (2010). Using body-anchored priors for identifying actions in single images. Neural Information Processing Systems. 23. 1072–1080. 3 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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