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2020 – today
- 2024
[c10]Hadar Mulian, Segev Shlomov, Lior Limonad, Alessia Noccaro, Silvia Buscaglione:
Mimicking the Maestro: Exploring the Efficacy of a Virtual AI Teacher in Fine Motor Skill Acquisition. AAAI 2024: 23224-23231- [c9]Segev Shlomov, Sami Marreed, Avi Yaeli:
Towards a Resilient Intelligent Automation System. IJCAI 2024: 8797-8800 - [i11]Alon Oved, Segev Shlomov, Sergey Zeltyn, Nir Mashkif, Avi Yaeli:
SNAP: Semantic Stories for Next Activity Prediction. CoRR abs/2401.15621 (2024) - [i10]Segev Shlomov, Avi Yaeli, Sami Marreed, Sivan Schwartz, Netanel Eder, Offer Akrabi, Sergey Zeltyn:
IDA: Breaking Barriers in No-code UI Automation Through Large Language Models and Human-Centric Design. CoRR abs/2407.15673 (2024) - [i9]Segev Shlomov, Ben Wiesel, Aviad Sela, Ido Levy, Liane Galanti, Roy Abitbol:
From Grounding to Planning: Benchmarking Bottlenecks in Web Agents. CoRR abs/2409.01927 (2024) - [i8]Ido Levy, Ben Wiesel, Sami Marreed, Alon Oved, Avi Yaeli, Segev Shlomov:
ST-WebAgentBench: A Benchmark for Evaluating Safety and Trustworthiness in Web Agents. CoRR abs/2410.06703 (2024) - 2023
- [i7]Sivan Schwartz, Avi Yaeli, Segev Shlomov:
Enhancing Trust in LLM-Based AI Automation Agents: New Considerations and Future Challenges. CoRR abs/2308.05391 (2023) - [i6]Segev Shlomov, Jonathan Muehlstein, Nitzan Guetta, Lior Limonad:
Ongoing Tracking of Engagement in Motor Learning. CoRR abs/2308.07670 (2023) - [i5]Hadar Mulian, Segev Shlomov, Lior Limonad:
Mimicking the Maestro: Exploring the Efficacy of a Virtual AI Teacher in Fine Motor Skill Acquisition. CoRR abs/2310.10280 (2023) - 2022
- [c8]Avi Yaeli, Segev Shlomov, Alon Oved, Sergey Zeltyn, Nir Mashkif:
Recommending Next Best Skill in Conversational Robotic Process Automation. BPM (Blockchain and RPA Forum) 2022: 215-230 - [c7]Sergey Zeltyn, Segev Shlomov, Avi Yaeli, Alon Oved:
Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestration. PMAI@IJCAI 2022: 49-60 - [i4]Naama Zwerdling, Segev Shlomov, Esther Goldbraich, George Kour, Boaz Carmeli, Naama Tepper, Inbal Ronen, Vitaly Zabershinsky, Ateret Anaby-Tavor:
Understanding the Properties of Generated Corpora. CoRR abs/2206.11219 (2022) - [i3]Sergey Zeltyn, Segev Shlomov, Avi Yaeli, Alon Oved:
Prescriptive Process Monitoring in Intelligent Process Automation with Chatbot Orchestration. CoRR abs/2212.06564 (2022) - 2021
- [j2]Itai Arieli, Yakov Babichenko, Segev Shlomov:
Virtually additive learning. J. Econ. Theory 197: 105322 (2021) - [j1]Yakov Babichenko, Segev Shlomov
:
Robust learning in social networks via matrix scaling. Oper. Res. Lett. 49(5): 720-727 (2021) - [c6]Ofer Lavi, Ella Rabinovich, Segev Shlomov, David Boaz, Inbal Ronen, Ateret Anaby-Tavor:
We've had this conversation before: A Novel Approach to Measuring Dialog Similarity. EMNLP (1) 2021: 1169-1177 - [i2]Ofer Lavi, Ella Rabinovich, Segev Shlomov, David Boaz, Inbal Ronen, Ateret Anaby-Tavor:
We've had this conversation before: A Novel Approach to Measuring Dialog Similarity. CoRR abs/2110.05780 (2021) - 2020
- [b1]Rotem Dror, Lotem Peled-Cohen, Segev Shlomov, Roi Reichart:
Statistical Significance Testing for Natural Language Processing. Synthesis Lectures on Human Language Technologies, Morgan & Claypool Publishers 2020, ISBN 978-3-031-01046-0 - [c5]Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich, Amir Kantor, George Kour, Segev Shlomov, Naama Tepper, Naama Zwerdling:
Do Not Have Enough Data? Deep Learning to the Rescue! AAAI 2020: 7383-7390
2010 – 2019
- 2019
- [c4]Rotem Dror, Segev Shlomov, Roi Reichart:
Deep Dominance - How to Properly Compare Deep Neural Models. ACL (1) 2019: 2773-2785 - [c3]Itai Arieli, Yakov Babichenko, Segev Shlomov:
Robust Non-Bayesian Social Learning. EC 2019: 549-550 - [i1]Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich, Amir Kantor, George Kour, Segev Shlomov, Naama Tepper, Naama Zwerdling:
Not Enough Data? Deep Learning to the Rescue! CoRR abs/1911.03118 (2019) - 2018
- [c2]Rotem Dror, Gili Baumer, Segev Shlomov, Roi Reichart:
The Hitchhiker's Guide to Testing Statistical Significance in Natural Language Processing. ACL (1) 2018: 1383-1392 - 2017
- [c1]Rotem Dror, Amir Kantor, Michael Masin, Segev Shlomov:
Set-SMAA for finding preferable multi-objective solutions. GECCO (Companion) 2017: 149-150
Coauthor Index
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last updated on 2024-11-20 21:55 CET by the dblp team
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