Yftah Ziser

463 total citations
15 papers, 225 citations indexed

About

Yftah Ziser is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Communication. According to data from OpenAlex, Yftah Ziser has authored 15 papers receiving a total of 225 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 1 paper in Communication. Recurrent topics in Yftah Ziser's work include Topic Modeling (12 papers), Natural Language Processing Techniques (8 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Yftah Ziser is often cited by papers focused on Topic Modeling (12 papers), Natural Language Processing Techniques (8 papers) and Domain Adaptation and Few-Shot Learning (6 papers). Yftah Ziser collaborates with scholars based in United Kingdom, Israel and South Korea. Yftah Ziser's co-authors include Roi Reichart, Shay B. Cohen, David Carmel, Nachshon Cohen, Alessandro Moschitti, Edoardo Maria Ponti, Anna Korhonen, Bonnie Webber, Yifu Qiu and Zheng Zhao and has published in prestigious journals such as Language Resources and Evaluation, Transactions of the Association for Computational Linguistics and Edinburgh Research Explorer (University of Edinburgh).

In The Last Decade

Yftah Ziser

15 papers receiving 212 citations

Peers

Yftah Ziser
Vishakh Padmakumar United States
Tong Niu United States
Naveen Arivazhagan United States
Saad Mahamood United Kingdom
Yassine Benajiba United States
Asahi Ushio United Kingdom
Kawin Ethayarajh United States
Vishakh Padmakumar United States
Yftah Ziser
Citations per year, relative to Yftah Ziser Yftah Ziser (= 1×) peers Vishakh Padmakumar

Countries citing papers authored by Yftah Ziser

Since Specialization
Citations

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

Fields of papers citing papers by Yftah Ziser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yftah Ziser

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

All Works

15 of 15 papers shown
1.
Ziser, Yftah, et al.. (2025). TSPRank: Bridging Pairwise and Listwise Methods with a Bilinear Travelling Salesman Model. Edinburgh Research Explorer (University of Edinburgh). 707–718. 1 indexed citations
2.
Qiu, Yifu, Zheng Zhao, Yftah Ziser, et al.. (2024). Are Large Language Model Temporally Grounded?. 7064–7083. 2 indexed citations
3.
Ziser, Yftah, et al.. (2023). Erasure of Unaligned Attributes from Neural Representations. Transactions of the Association for Computational Linguistics. 11. 488–510. 2 indexed citations
4.
Qiu, Yifu, Yftah Ziser, Anna Korhonen, Edoardo Maria Ponti, & Shay B. Cohen. (2023). Detecting and Mitigating Hallucinations in Multilingual Summarisation. Edinburgh Research Explorer (University of Edinburgh). 8914–8932. 4 indexed citations
5.
Ziser, Yftah, Bonnie Webber, & Shay B. Cohen. (2023). Rant or rave: variation over time in the language of online reviews. Language Resources and Evaluation. 57(3). 1329–1359. 2 indexed citations
6.
7.
Ziser, Yftah, et al.. (2022). Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents. 6341–6364. 6 indexed citations
8.
Zhao, Zheng, Yftah Ziser, & Shay B. Cohen. (2022). Understanding Domain Learning in Language Models Through Subpopulation Analysis. 192–209. 2 indexed citations
9.
Ziser, Yftah, et al.. (2021). DILBERT: Customized Pre-Training for Domain Adaptation with Category Shift, with an Application to Aspect Extraction. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 219–230. 16 indexed citations
10.
Cohen, Nachshon, et al.. (2021). WikiSum: Coherent Summarization Dataset for Efficient Human-Evaluation. 212–219. 8 indexed citations
11.
Ziser, Yftah, et al.. (2020). Humor Detection in Product Question Answering Systems. 519–528. 10 indexed citations
12.
Ziser, Yftah & Roi Reichart. (2019). Task Refinement Learning for Improved Accuracy and Stability of Unsupervised Domain Adaptation. 5895–5906. 22 indexed citations
13.
Ziser, Yftah & Roi Reichart. (2018). Deep Pivot-Based Modeling for Cross-language Cross-domain Transfer with Minimal Guidance. 238–249. 21 indexed citations
14.
Ziser, Yftah & Roi Reichart. (2018). Pivot Based Language Modeling for Improved Neural Domain Adaptation. 1241–1251. 67 indexed citations
15.
Ziser, Yftah & Roi Reichart. (2017). Neural Structural Correspondence Learning for Domain Adaptation. 400–410. 59 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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