Results suggest that localized multi-agent automation can make time-series modeling easier, and significantly reduces measured per-run cost, while staying within a comparable energy consumption.
This tutorial provides the foundations for building auditable, production-grade agents for Industry 4.0 through end to end MCP grounded agent pipeline that connects specialized MCP servers to high velocity industrial data.
Dhaval Patel, Chathurangi Shyalika, Shuxin Lin et al.· Proceedings of the 32nd ACM...· 0 citations
Results show that MAGen translates generic LLM competence into reproducible, automation-ready contract-and-test artifacts under a fixed validation protocol.
Lixue Liu, Wei Ke, Haiyang Chi et al.· Empirical Software Engineeri...· 0 citations
A multi-agent collaborative framework, StarVerus, to automate the verification of industrial Rust code and introduces a planner-repairer-actor-rewriter multi-agent paradigm to further enhance the proof repair capabilities.
Chao Jiang, Ding Wang, Dugang Liu et al.· Proceedings of the 32nd ACM...· 0 citations
Real-time automation of financial activities, including approvals, controls, routing, and monitoring, can enable fast response to opportunities and threats, eliminating the rotation of capital through liquidity provider balances and streamlining interactions with sources of capital. Generative and agentic AI technologies, supported by real-time data streams of events, market feeds, and key risk indicators, can automate and govern these transactions provided that high standards of latency, throughput, security, and regulatory compliance are achieved. A cloud-native DevOps ecosystem equipped with serverless infrastructure-as-code patterns ensures scalable, cost-effective operations with minimum user interference, allowing a comprehensive evaluation of operational performance, change management, security controls, and regulatory oversight. Scenarios involving AI agents as the driving or supervisory part of automation workflows illustrate the architectural paradigm. The analysis identifies the expected challenges in operational responsibility and response reliability, gathering additional evidence from existing Cloud-Native/Serverless solutions of similar scope. Mitigation strategies address the main issues encountered in every-day AI adoption and propose supporting operations management and security controls. The examination of the full end-to-end process flow, including off-line and real-time phases, ensures cover for Governance, Risk, and Compliance (GRC) objectives by design and the definition of a robust plan for evaluation in on-line use.
E. Campbell· American International Journ...· 0 citations
CyberLLM is presented, a multi-agent, LLM-orchestrated framework that autonomously detects vulnerabilities and executes remediations under a formal, runtime safety guard, and indicates that LLM agents can perform useful autonomous cyber-defense when wrapped in a deterministic, auditable safety envelope.
Nenad Petrovic, Oussama Jeddou, Feres Ben Fraj et al.· 0 citations
This work introduces AgentS4D, a sandboxed benchmark for lifecycle-wide runtime safety evaluation and evaluates all 20 combinations of four harnesses and five LLM backends, finding that the observed safety of an agent system varies with both its harness-LLM pairing and how risk is introduced.
Jiajun Zhou, Zhaoxuan Ke, Jihang Ye et al.· arXiv.org· 1 citation
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