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researcher

Mor Shpigel Nacson

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.AI2
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedGradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2026

Adaptive Influence Graphs for Failure Attribution in Multi-Agent Systems

Yarden Bakish, Amir Dudai, Roy Ganz +4

Multi-agent LLM systems are increasingly deployed in real-world applications, where failures can be costly and difficult to localize. Despite growing efforts to automate failure at…

cs.AI2026

The Handoff Tax: Continuing Non-Native Trajectories in LLM Agents

Roy Ganz, Mor Shpigel Nacson, Adi Kalyanpur +1

Coding agents perform long-running tasks spanning dozens of model calls, tool uses, and code edits. As these runs unfold, users face a practical cost-quality trade-off: escalating…

cs.LG2023★ 1 cited

Gradient Descent Monotonically Decreases the Sharpness of Gradient Flow Solutions in Scalar Networks and Beyond

Itai Kreisler, Mor Shpigel Nacson, Daniel Soudry +1

Recent research shows that when Gradient Descent (GD) is applied to neural networks, the loss almost never decreases monotonically. Instead, the loss oscillates as gradient descent…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.