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ORCIDNatalia Vanetik
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2020 – today
- 2024
[j14]Matan Davidian, Michael Kiperberg, Natalia Vanetik
:
Early Ransomware Detection with Deep Learning Models. Future Internet 16(8): 291 (2024)- [j13]Natalia Vanetik, Margarita Tiamanova, Genady Kogan, Marina Litvak:
Genre Classification of Books in Russian with Stylometric Features: A Case Study. Inf. 15(6): 340 (2024) - [c32]Dingxin Hu, Xuanyu Zhang, Xingyue Zhang, Yiyang Li, Dongsheng Chen, Marina Litvak, Natalia Vanetik, Qing Yang, Dongliang Xu, Yanquan Zhou, Lei Li, Yuze Li, Yingqi Zhu:
Improving Factual Consistency in Abstractive Summarization with Sentence Structure Pruning. LREC/COLING 2024: 8792-8803 - [i6]Yiyang Li, Lei Li, Dingxin Hu, Xueyi Hao, Marina Litvak, Natalia Vanetik, Yanquan Zhou:
Improving Factual Error Correction for Abstractive Summarization via Data Distillation and Conditional-generation Cloze. CoRR abs/2402.08581 (2024) - 2023
- [j12]Natalia Vanetik:
Sufficient Networks for Computing Support of Graph Patterns. Inf. 14(3): 143 (2023) - [j11]Natalia Vanetik, Genady Kogan:
Job Vacancy Ranking with Sentence Embeddings, Keywords, and Named Entities. Inf. 14(8): 468 (2023) - [c31]Natalia Vanetik, Elizaveta Podkaminer, Marina Litvak:
Summarizing Financial Reports with Positional Language Model. IEEE Big Data 2023: 2877-2883 - [c30]Natalia Vanetik, Marina Litvak, Lin Miao:
Cross-lingual Transfer Learning for Detecting Negative Campaign in Israeli Municipal Elections: a Case Study. Text2Story@ECIR 2023: 83-92 - [c29]Natalia Vanetik, Alona Kolesnev, Genady Kogan:
NLP-based Screening for IT Job Vacancies: A Case Study. IACT@SIGIR 2023: 13-22 - [c28]Natalia Vanetik, Marina Litvak, Egor Reviakin, Margarita Tiamanova:
Propaganda Detection in Russian Telegram Posts in the Scope of the Russian Invasion of Ukraine. RANLP 2023: 1162-1170 - [c27]Nadav Ishai, Dolev Peretz, Natalia Vanetik, Marina Litvak:
Teledermatologist: Automated Diagnosis of Skin Diseases with Image Recognition. VCIP 2023: 1 - 2022
- [j10]Natalia Vanetik, Elisheva Mimoun:
Detection of Racist Language in French Tweets. Inf. 13(7): 318 (2022) - [j9]Natalia Vanetik:
Graph support measures and flows. Soc. Netw. Anal. Min. 12(1): 120 (2022) - [c26]Matan Davidian, Natalia Vanetik, Michael Kiperberg:
Ransomware Detection with Deep Neural Networks. ICISSP 2022: 656-663 - [c25]Siya Qi, Lei Li, Yiyang Li, Jin Jiang, Dingxin Hu, Yuze Li, Yingqi Zhu, Yanquan Zhou, Marina Litvak, Natalia Vanetik:
SAPGraph: Structure-aware Extractive Summarization for Scientific Papers with Heterogeneous Graph. AACL/IJCNLP (1) 2022: 575-586 - [c24]Marina Litvak, Natalia Vanetik, Chaya Liebeskind, Omar Hmdia, Rizek Abu Madeghem:
Offensive language detection in Hebrew: can other languages help? LREC 2022: 3715-3723 - [i5]Yiyang Li, Lei Li, Qing Yang, Marina Litvak, Natalia Vanetik, Dingxin Hu, Yuze Li, Yanquan Zhou, Dongliang Xu, Xuanyu Zhang:
Just ClozE! A Fast and Simple Method for Evaluating the Factual Consistency in Abstractive Summarization. CoRR abs/2210.02804 (2022) - 2021
- [i4]Lei Li, Wei Liu, Marina Litvak, Natalia Vanetik, Jiacheng Pei, Yinan Liu, Siya Qi:
Subjective Bias in Abstractive Summarization. CoRR abs/2106.10084 (2021) - 2020
- [j8]Natalia Vanetik, Marina Litvak, Elena Churkin, Mark Last:
An unsupervised constrained optimization approach to compressive summarization. Inf. Sci. 509: 22-35 (2020) - [c23]Natalia Vanetik, Marina Litvak, Sergey Shevchuk, Lior Reznik:
Automated Discovery of Mathematical Definitions in Text. LREC 2020: 2086-2094 - [i3]Natalia Vanetik, Marina Litvak, Sergey Shevchuk, Lior Reznik:
Automated Discovery of Mathematical Definitions in Text with Deep Neural Networks. CoRR abs/2011.04521 (2020)
2010 – 2019
- 2019
- [c22]Marina Litvak, Natalia Vanetik, Yael Veksler:
EASY: Evaluation System for Summarization. CICLing (2) 2019: 529-545 - [c21]Lei Li, Wei Liu, Marina Litvak, Natalia Vanetik, Zuying Huang:
In Conclusion Not Repetition: Comprehensive Abstractive Summarization with Diversified Attention Based on Determinantal Point Processes. CoNLL 2019: 822-832 - [c20]Lei Li, Zuying Huang, Natalia Vanetik, Marina Litvak:
Quality-Diversity Summarization with Unsupervised Autoencoders. ICANN (4) 2019: 293-299 - [i2]Lei Li, Wei Liu, Marina Litvak, Natalia Vanetik, Zuying Huang:
In Conclusion Not Repetition: Comprehensive Abstractive Summarization With Diversified Attention Based On Determinantal Point Processes. CoRR abs/1909.10852 (2019) - 2018
- [c19]Elena Churkin, Mark Last, Marina Litvak, Natalia Vanetik:
Sentence Compression as a Supervised Learning with a Rich Feature Space. CICLing (2) 2018: 261-271 - [c18]Natalia Vanetik, Marina Litvak:
DRIM: MDL-Based Approach for Fast Diverse Summarization. WI 2018: 660-663 - [c17]Marina Litvak, Natalia Vanetik, Itzhak Eretz Kdosha:
HEvaS: Headline Evaluation System. WI 2018: 664-667 - 2017
- [c16]Marina Litvak, Natalia Vanetik:
Query-based summarization using MDL principle. MultiLing@EACL 2017: 22-31 - [c15]Marina Litvak, Natalia Vanetik, Lei Li:
Summarizing Weibo with Topics Compression. CICLing (2) 2017: 522-534 - 2016
- [c14]Marina Litvak, Natalia Vanetik, Mark Last, Elena Churkin:
MUSEEC: A Multilingual Text Summarization Tool. ACL (System Demonstrations) 2016: 73-78 - [c13]Marina Litvak, Natalia Vanetik, Efi Levi, Michael Roistacher:
What's up on Twitter? Catch up with TWIST! COLING (Demos) 2016: 213-217 - 2015
- [c12]Marina Litvak, Natalia Vanetik, Chunlei Liu, Lemin Xiao, Onur Savas:
Improving Summarization Quality with Topic Modeling. TM@CIKM 2015: 39-47 - [c11]Marina Litvak, Mark Last, Natalia Vanetik:
Krimping texts for better summarization. EMNLP 2015: 1931-1935 - [c10]Natalia Vanetik, Marina Litvak:
Multilingual Summarization with Polytope Model. SIGDIAL Conference 2015: 227-231 - 2014
- [j7]Chen Yanover, Natalia Vanetik, Michael Levitt, Rachel Kolodny, Chen Keasar:
Redundancy-weighting for better inference of protein structural features. Bioinform. 30(16): 2295-2301 (2014) - [j6]Marina Litvak, Natalia Vanetik:
Multi-document Summarization using Tensor Decomposition. Computación y Sistemas 18(3) (2014) - 2013
- [c9]Marina Litvak, Natalia Vanetik:
Mining the Gaps: Towards Polynomial Summarization. IJCNLP 2013: 655-660 - 2012
- [j5]Natalia Vanetik:
On the fractionality of the path packing problem. J. Comb. Optim. 24(4): 526-539 (2012) - [c8]Marina Litvak, Natalia Vanetik:
Polytope Model for Extractive Summarization. KDIR 2012: 281-286 - [c7]Natalia Vanetik:
Classification of Datasets with Frequent Itemsets is Wild. KDIR 2012: 386-389 - 2011
- [c6]Natalia Vanetik:
A Fast Algorithm for Mining Graphs of Prescribed Connectivity. KDIR 2011: 5-13 - [c5]Natalia Vanetik:
Mining Graphs of Prescribed Connectivity. IC3K 2011: 29-44 - [c4]Natalia Vanetik, Ehud Gudes:
HashMax: A New Method for Mining Maximal Frequent Itemsets. KDIR 2011: 140-145 - 2010
- [c3]Natalia Vanetik:
Mining Graphs with Constraints on Symmetry and Diameter. WAIM Workshops 2010: 1-12
2000 – 2009
- 2009
- [j4]Vladimir Lipets, Natalia Vanetik, Ehud Gudes:
Subsea: an efficient heuristic algorithm for subgraph isomorphism. Data Min. Knowl. Discov. 19(3): 320-350 (2009) - [j3]Natalia Vanetik:
Path packing and a related optimization problem. J. Comb. Optim. 17(2): 192-205 (2009) - 2008
- [i1]Natalia Vanetik:
On fractionality of the path packing problem. CoRR abs/0809.3565 (2008) - 2006
- [j2]Natalia Vanetik, Solomon Eyal Shimony, Ehud Gudes:
Support measures for graph data. Data Min. Knowl. Discov. 13(2): 243-260 (2006) - [j1]Ehud Gudes, Solomon Eyal Shimony, Natalia Vanetik:
Discovering Frequent Graph Patterns Using Disjoint Paths. IEEE Trans. Knowl. Data Eng. 18(11): 1441-1456 (2006) - 2004
- [c2]Natalia Vanetik, Ehud Gudes:
Mining Frequent Labeled and Partially Labeled Graph Patterns. ICDE 2004: 91-102 - 2002
- [c1]Natalia Vanetik, Ehud Gudes, Solomon Eyal Shimony:
Computing Frequent Graph Patterns from Semistructured Data. ICDM 2002: 458-465
Coauthor Index
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