no code implementations • EMNLP 2021 • Ofer Lavi, Ella Rabinovich, Segev Shlomov, David Boaz, Inbal Ronen, Ateret Anaby Tavor
The results demonstrate that our method outperforms the other approaches in capturing dialog flow, and is better aligned with the human perception of conversation similarity.
no code implementations • 28 Jan 2024 • Alon Oved, Segev Shlomov, Sergey Zeltyn, Nir Mashkif, Avi Yaeli
To address this gap, we propose the novel SNAP method that leverages language foundation models by constructing semantic contextual stories from the process historical event logs and using them for the next activity prediction.
no code implementations • 16 Oct 2023 • Hadar Mulian, Segev Shlomov, Lior Limonad, Alessia Noccaro, Silvia Buscaglione
In this study, we examine the potential of a virtual AI teacher in emulating the techniques of human educators for motor skill acquisition.
no code implementations • 10 Aug 2023 • Sivan Schwartz, Avi Yaeli, Segev Shlomov
This paper explores these new challenges and opportunities, analyzes the main aspects of trust in AI agents discussed in existing literature, and identifies specific considerations and challenges relevant to this new generation of automation agents.
1 code implementation • 13 Dec 2022 • Sergey Zeltyn, Segev Shlomov, Avi Yaeli, Alon Oved
Using this dataset, we demonstrate crowd-wisdom and goal-driven approaches to prescriptive process monitoring.
no code implementations • 22 Jun 2022 • Naama Zwerdling, Segev Shlomov, Esther Goldbraich, George Kour, Boaz Carmeli, Naama Tepper, Inbal Ronen, Vitaly Zabershinsky, Ateret Anaby-Tavor
Models for text generation have become focal for many research tasks and especially for the generation of sentence corpora.
no code implementations • 12 Oct 2021 • Ofer Lavi, Ella Rabinovich, Segev Shlomov, David Boaz, Inbal Ronen, Ateret Anaby-Tavor
The results demonstrate that our method outperforms the other approaches in capturing dialog flow, and is better aligned with the human perception of conversation similarity.
no code implementations • 7 Mar 2021 • Charles-Albert Lehalle, Eyal Neuman, Segev Shlomov
In addition to the classical framework, a revenue term is added to the market maker's performance function, which is proportional to the order flow and to the size of the bid-ask spread.
1 code implementation • 8 Nov 2019 • Ateret Anaby-Tavor, Boaz Carmeli, Esther Goldbraich, Amir Kantor, George Kour, Segev Shlomov, Naama Tepper, Naama Zwerdling
Based on recent advances in natural language modeling and those in text generation capabilities, we propose a novel data augmentation method for text classification tasks.
1 code implementation • ACL 2019 • Rotem Dror, Segev Shlomov, Roi Reichart
Comparing between Deep Neural Network (DNN) models based on their performance on unseen data is crucial for the progress of the NLP field.
1 code implementation • ACL 2018 • Rotem Dror, Gili Baumer, Segev Shlomov, Roi Reichart
We establish the fundamental concepts of significance testing and discuss the specific aspects of NLP tasks, experimental setups and evaluation measures that affect the choice of significance tests in NLP research.