Assaf Arbelle

729 total citations
11 papers, 195 citations indexed

About

Assaf Arbelle is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Assaf Arbelle has authored 11 papers receiving a total of 195 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 1 paper in Computational Theory and Mathematics. Recurrent topics in Assaf Arbelle's work include Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Advanced Vision and Imaging (2 papers). Assaf Arbelle is often cited by papers focused on Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers) and Advanced Vision and Imaging (2 papers). Assaf Arbelle collaborates with scholars based in United States, Israel and Germany. Assaf Arbelle's co-authors include Leonid Karlinsky, Rogério Feris, Rameswar Panda, Donghyun Kim, Paola Cascante-Bonilla, Zsolt Kira, James Smith, Tammy Riklin Raviv, Eli Schwartz and Raja Giryes and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Medical Image Analysis and Computer Vision and Image Understanding.

In The Last Decade

Assaf Arbelle

10 papers receiving 192 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Assaf Arbelle United States	7	117	102	22	15	10	11	195
Suraj Srinivas India	4	113 1.0×	91 0.9×	6 0.3×	7 0.5×	10 1.0×	10	166
Jiří Borovec Czechia	6	69 0.6×	77 0.8×	13 0.6×	22 1.5×	29 2.9×	10	173
Jingyi Xu China	6	142 1.2×	92 0.9×	20 0.9×	5 0.3×	21 2.1×	13	224
Victor Pomponiu Italy	10	139 1.2×	175 1.7×	19 0.9×	10 0.7×	40 4.0×	21	319
Raphael Gontijo Lopes United States	3	180 1.5×	179 1.8×	10 0.5×	4 0.3×	18 1.8×	5	272
Leiguang Gong United States	8	76 0.6×	112 1.1×	9 0.4×	8 0.5×	18 1.8×	29	191
Utkarsh Ojha United States	4	81 0.7×	228 2.2×	25 1.1×	9 0.6×	13 1.3×	9	271
Alan Anwer Abdulla Iraq	11	83 0.7×	285 2.8×	50 2.3×	11 0.7×	51 5.1×	18	323
Nikunj Saunshi United States	4	141 1.2×	62 0.6×	6 0.3×	4 0.3×	5 0.5×	8	181

Countries citing papers authored by Assaf Arbelle

Since Specialization

Citations

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

Fields of papers citing papers by Assaf Arbelle

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Assaf Arbelle

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

All Works

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11 of 11 papers shown

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

Schwartz, Eli, Assaf Arbelle, Leonid Karlinsky, et al.. (2024). MAEDAY: MAE for few- and zero-shot AnomalY-Detection. Computer Vision and Image Understanding. 241. 103958–103958. 16 indexed citations

Herzig, Roei, Assaf Arbelle, Leonid Karlinsky, et al.. (2024). PromptonomyViT: Multi-Task Prompt Learning Improves Video Transformers using Synthetic Scene Data. 6789–6801. 2 indexed citations

Arbelle, Assaf, et al.. (2024). Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning. 22124–22153.

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

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

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

Arbelle, Assaf, et al.. (2023). Differentiable Histogram Loss Functions for Intensity-based Image-to-Image Translation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(10). 11642–11653. 11 indexed citations

Smith, James, Leonid Karlinsky, Paola Cascante-Bonilla, et al.. (2023). CODA-Prompt: COntinual Decomposed Attention-Based Prompting for Rehearsal-Free Continual Learning. 11909–11919. 93 indexed citations

10.

Harary, Sivan, Eli Schwartz, Assaf Arbelle, et al.. (2022). Unsupervised Domain Generalization by Learning a Bridge Across Domains. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 5270–5280. 18 indexed citations

11.

Arbelle, Assaf, José Reyes, Jia-Yun Chen, Galit Lahav, & Tammy Riklin Raviv. (2018). A probabilistic approach to joint cell tracking and segmentation in high-throughput microscopy videos. Medical Image Analysis. 47. 140–152. 21 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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