arXiv AI By Yusheng Zheng, Chaokun Chang, Yu Mao, Tianyuan Wu, Yuxi Huang, Tao Ma, Wenan Mao, Shuyi Cheng, Andi Quinn, Wei Wang

AgentPProf: Semantic Profiler for Long Horizon AI Agents

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AgentPProf is a new semantic profiler designed for long‑horizon AI agents that aggregates agent trajectories into pprof‑compatible profiles, enabling flame‑graph visualization and hierarchical attribution of tasks and subtasks. It introduces a semantic operation stack model and recursive operation segmentation to replace traditional call‑stack profiling, addressing the challenge of profiling agent intent rather than code paths. In evaluations, AgentPProf achieves high F1 scores against human annotations and significantly improves problem‑localization metrics, demonstrating its effectiveness in attributing resources, locating issues, and optimizing token cost.

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arXiv Machine Learning
1d ago

TRACE: Tackling Real-World Resource Assignment Problems via Agentic Heuristic Design

TRACE tackles real‑world dynamic resource assignment by combining evolutionary automatic heuristic design with an agentic knowledge‑extraction workflow. A Reasoner agent interprets system logs to hypothesize about underlying dynamics, while a Coder agent generates and runs schema‑specific code to validate these hypotheses, producing insights or executable tools for the evolved heuristics. Evaluations on a synthetic cloud benchmark and a 5G vRAN scenario show that TRACE outperforms existing AHD methods, delivering more auditable heuristics with less than 2% overhead.

By Jose A. Ayala-Romero, Andres Garcia-Saavedra, Xavier Costa-Perez