arXiv AI

A T-API-Compliant ReAct Agentic Loop for Optical Networks: Generic vs. Domain-Specific Tool Abstractions

arXiv:2606. 18000v1 Announce Type: cross Abstract: Optical networks need intent-driven, closed-loop agentic management, a key enabler for higher autonomy levels.

arXiv AI
2d ago

LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios

The article surveys LLM-based agentic reasoning frameworks, presenting a unified formal language that categorizes them into single-agent, tool-based, and multi-agent methods. It reviews application scenarios in scientific discovery, healthcare, software engineering, society, economics, and general-purpose tasks, and compares the distinct features and evaluation strategies of each category. The survey highlights the rapid development of complex agentic systems in real-world contexts.

By Bingxi Zhao, Lin Geng Foo, Ping Hu, Christian Theobalt, Hossein Rahmani, Jun Liu
arXiv AI
4d ago

Agentic AI for Scalable and Robust Optical Systems Control

arXiv:2602.20144v2 Announce Type: replace-cross Abstract: We present AgentOptics, an agentic AI framework for high-fidelity, autonomous optical system control built on the Model Context Protocol (MCP...

By Zehao Wang, Mingzhe Han, Wei Cheng, Yue-Kai Huang, Philip Ji, Denton Wu, Mahdi Safari, Flemming Holtorf, Kenaish AlQubaisi, Norbert M. Linke, Danyang Zhuo, Yiran Chen, Ting Wang, Dirk Englund, Tingjun Chen
arXiv AI
Aug 6

Terminal Agents Suffice for Enterprise Automation

arXiv:2604. 00073v3 Announce Type: replace-cross Abstract: There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomously.

By Patrice Bechard, Orlando Marquez Ayala, Emily Chen, Jordan Skelton, Sagar Davasam, Srinivas Sunkara, Vikas Yadav, Sai Rajeswar
arXiv AI
Jul 22

Agents in the Wild: Where Research Meets Deployment

arXiv:2607. 19336v1 Announce Type: new Abstract: Agentic systems large language model (LLM) based architectures capable of reasoning, planning, acting, and coordinating with tools and other agents are rapidly transitioning from research prototypes to production scale deployments across domains such as software engineering, scientific discovery, and finance.

By Grace Hui Yang, Pranav N. Venkit, Hooman Sedghamiz, Enrico Santus, Victor Dibia, Ioana Baldini
arXiv AI
Aug 13

Self-evolving network verifiers

arXiv:2608. 11340v1 Announce Type: cross Abstract: Symbolic network verifiers can reason about correctness across vast spaces of routing inputs and failures, but only for the protocols and features an expert has encoded by hand.

By Ioannis Protogeros, Tibor Schneider, Laurent Vanbever
arXiv AI
Sep 7

Octopus Protocol: One-Shot Hardware Discovery and Control for AI Agents via Infrastructure-as-Prompts

Octopus Protocol is a hardware onboarding framework that allows an AI coding agent to automatically discover, identify, and integrate hardware devices into an AI system. Using a single bootstrap command, the agent runs a five-stage pipeline to enumerate visible hardware, infer device capabilities, generate typed Model Context Protocol tools, produce the necessary code, and activate a live endpoint. The system maintains a persistent daemon that repairs deployment failures, enabling consistent, platform‑agnostic interfaces across diverse hosts without manual integration code.

By Quilee Simeon, Justin M. Wei, Yile Fan