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Segev Shlomov
Segev Shlomov
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Title
Cited by
Cited by
Year
The hitchhiker’s guide to testing statistical significance in natural language processing
R Dror, G Baumer, S Shlomov, R Reichart
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
2462018
Do not have enough data? Deep learning to the rescue!
A Anaby-Tavor, B Carmeli, E Goldbraich, A Kantor, G Kour, S Shlomov, ...
Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7383-7390, 2020
1282020
Deep dominance-how to properly compare deep neural models
R Dror, S Shlomov, R Reichart
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
422019
Statistical significance testing for natural language processing
R Dror, L Peled-Cohen, S Shlomov, R Reichart
Synthesis Lectures on Human Language Technologies 13 (2), 1-116, 2020
302020
Not enough data
A Anaby-Tavor, B Carmeli, E Goldbraich, A Kantor, G Kour, S Shlomov, ...
Deep learning to the rescue, 1911
61911
Robust non-Bayesian social learning
I Arieli, Y Babichenko, S Shlomov
Proceedings of the 2019 ACM Conference on Economics and Computation, 549-550, 2019
42019
We've had this conversation before: A Novel Approach to Measuring Dialog Similarity
O Lavi, E Rabinovich, S Shlomov, D Boaz, I Ronen, A Anaby-Tavor
arXiv preprint arXiv:2110.05780, 2021
12021
Virtually additive learning
I Arieli, Y Babichenko, S Shlomov
Journal of Economic Theory 197, 105322, 2021
12021
Pareto-efficient probabilistic solutions
A Kantor, M Masin, S Shlomov, R Dror
US Patent App. 15/905,988, 2019
12019
Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestration
S Zeltyn, S Shlomov, A Yaeli, A Oved
International Joint Conference on Artificial Intelligence, 2022
2022
Understanding the Properties of Generated Corpora
N Zwerdling, S Shlomov, E Goldbraich, G Kour, B Carmeli, N Tepper, ...
arXiv preprint arXiv:2206.11219, 2022
2022
Language-model-based data augmentation method for textual classification tasks with little data
A Kantor, AA Tavor, B Carmeli, E Goldbraich, G Kour, S Shlomov, ...
US Patent App. 16/870,917, 2021
2021
Robust learning in social networks via matrix scaling
Y Babichenko, S Shlomov
Operations Research Letters 49 (5), 720-727, 2021
2021
Phase Transitions in Kyle's Model with Market Maker Profit Incentives
CA Lehalle, E Neuman, S Shlomov
arXiv preprint arXiv:2103.04481, 2021
2021
General Contact Process with Rapid Stirring
L Mytnik, S Shlomov
ALEA 18, 17-33, 2021
2021
Statistical Significance Tests
R Dror, L Peled-Cohen, S Shlomov, R Reichart
Statistical Significance Testing for Natural Language Processing, 9-21, 2020
2020
Open Questions and Challenges
R Dror, L Peled-Cohen, S Shlomov, R Reichart
Statistical Significance Testing for Natural Language Processing, 75-77, 2020
2020
Deep Significance
R Dror, L Peled-Cohen, S Shlomov, R Reichart
Statistical Significance Testing for Natural Language Processing, 35-50, 2020
2020
Statistical Hypothesis Testing
R Dror, L Peled-Cohen, S Shlomov, R Reichart
Statistical Significance Testing for Natural Language Processing, 3-7, 2020
2020
Replicability Analysis
R Dror, L Peled-Cohen, S Shlomov, R Reichart
Statistical Significance Testing for Natural Language Processing, 51-73, 2020
2020
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