Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Shlomov, Segev"'
Recent advancements in LLM-based web agents have introduced novel architectures and benchmarks showcasing progress in autonomous web navigation and interaction. However, most existing benchmarks prioritize effectiveness and accuracy, overlooking cruc
Externí odkaz:
http://arxiv.org/abs/2410.06703
General web-based agents are increasingly essential for interacting with complex web environments, yet their performance in real-world web applications remains poor, yielding extremely low accuracy even with state-of-the-art frontier models. We obser
Externí odkaz:
http://arxiv.org/abs/2409.01927
Autor:
Shlomov, Segev, Yaeli, Avi, Marreed, Sami, Schwartz, Sivan, Eder, Netanel, Akrabi, Offer, Zeltyn, Sergey
Business users dedicate significant amounts of time to repetitive tasks within enterprise digital platforms, highlighting a critical need for automation. Despite advancements in low-code tools for UI automation, their complexity remains a significant
Externí odkaz:
http://arxiv.org/abs/2407.15673
Predicting the next activity in an ongoing process is one of the most common classification tasks in the business process management (BPM) domain. It allows businesses to optimize resource allocation, enhance operational efficiency, and aids in risk
Externí odkaz:
http://arxiv.org/abs/2401.15621
Publikováno v:
EAAI Symposium: AI for Education 2024
Motor skills, especially fine motor skills like handwriting, play an essential role in academic pursuits and everyday life. Traditional methods to teach these skills, although effective, can be time-consuming and inconsistent. With the rise of advanc
Externí odkaz:
http://arxiv.org/abs/2310.10280
Teaching motor skills such as playing music, handwriting, and driving, can greatly benefit from recently developed technologies such as wearable gloves for haptic feedback or robotic sensorimotor exoskeletons for the mediation of effective human-huma
Externí odkaz:
http://arxiv.org/abs/2308.07670
Trust in AI agents has been extensively studied in the literature, resulting in significant advancements in our understanding of this field. However, the rapid advancements in Large Language Models (LLMs) and the emergence of LLM-based AI agent frame
Externí odkaz:
http://arxiv.org/abs/2308.05391
Business processes that involve AI-powered automation have been gaining importance and market share in recent years. These business processes combine the characteristics of classical business process management, goal-driven chatbots, conversational r
Externí odkaz:
http://arxiv.org/abs/2212.06564
Autor:
Zwerdling, Naama, Shlomov, Segev, Goldbraich, Esther, Kour, George, Carmeli, Boaz, Tepper, Naama, Ronen, Inbal, Zabershinsky, Vitaly, Anaby-Tavor, Ateret
Models for text generation have become focal for many research tasks and especially for the generation of sentence corpora. However, understanding the properties of an automatically generated text corpus remains challenging. We propose a set of tools
Externí odkaz:
http://arxiv.org/abs/2206.11219
Dialog is a core building block of human natural language interactions. It contains multi-party utterances used to convey information from one party to another in a dynamic and evolving manner. The ability to compare dialogs is beneficial in many rea
Externí odkaz:
http://arxiv.org/abs/2110.05780