arXiv (All)
open access
AgentWeave: Efficient Distributed Agent Serving via Flow Decomposition
Agent applications are evolving into workflows composed of large language model (LLM) calls and tool invocations, termed modules. Existing distributed agent systems typically adopt a disaggregated architecture, deploying different modules on separate devices. While this enables pipeline parallelism,
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Scepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines#1105012
- Engineering Sustainable Agents: A Systematic Comparison of Agentic LLMs for Developer Workflows#1187688
- Engineering Sustainable Agents: A Systematic Comparison of Agentic LLMs for Developer Workflows#1181704
- OrchSLM: Probing the Dynamics of Small Language Model Orchestration#1071256
- Can Agent Harnesses and Inference Engines Hear Each Other? The HEAR Protocol for Agentic LLM Serving#1215694
Record · ID 1325700
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive