3 papers
cs.AI2026
MoFlow: Multi-Objective Agentic Workflow Generation
Yining Lu, Aurelie Lozano, Xi Yang +3
We study the generation of agentic workflows that jointly optimize multiple objectives, such as accuracy, cost, latency, robustness, and consistency. Existing methods for workflow…
cs.AI2026
A Context Engineering Framework for Improving Enterprise AI Agents based on Digital-Twin MDP
Xi Yang, Aurelie Lozano, Naoki Abe +6
Despite rapid progress in AI agents for enterprise automation and decision-making, their real-world deployment and further performance gains remain constrained by limited data qual…
cs.LG2024
Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes
Dongxia Wu, Tsuyoshi Idé, Aurélie Lozano +5
We address the problem of learning Granger causality from asynchronous, interdependent, multi-type event sequences. In particular, we are interested in discovering instance-level c…