2 citations · 3 across the 4 of their papers we have counts for
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cs.AI2026
Semantic Feature Analysis: Improving Agents Without Searching Over Rollouts
Roi Ben-Gigi, Yuval David, Fabiana Fournier +4
Ambiguity is an inherent property of natural-language agent specifications. When a system prompt leaves behaviour underdetermined, identical inputs follow divergent execution paths…
cs.AI2025★ 2 cited
Taming Uncertainty via Automation: Observing, Analyzing, and Optimizing Agentic AI Systems
Dany Moshkovich, Sergey Zeltyn
Large Language Models (LLMs) are increasingly deployed within agentic systems - collections of interacting, LLM-powered agents that execute complex, adaptive workflows using memory…
cs.AI2025★ 1 cited
Beyond Black-Box Benchmarking: Observability, Analytics, and Optimization of Agentic Systems
Dany Moshkovich, Hadar Mulian, Sergey Zeltyn +3
The rise of agentic AI systems, where agents collaborate to perform diverse tasks, poses new challenges with observing, analyzing and optimizing their behavior. Traditional evaluat…