arXiv (All)
open access
Large Language Model Orchestration under Heterogeneous Preferences via Explicit Persona Inference
LLM orchestration investigates how an orchestrator coordinates a group of autonomous agents to achieve common goals or maximize collective welfare. The agents are typically heterogeneous, each holding a private preference that it pursues but does not reveal. Inferring such hidden preferences from be
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
- Pretrained Persona Mixture Models and Tandem Models for Human Simulation#1037290
- Fairness Testing of Large Language Models in Role-Playing#158647
- SwarmBench: Can Large Language Models Act as Agent Swarm Orchestrators?#818717
- SwarmBench: Can Large Language Models Act as Agent Swarm Orchestrators?#808725
- PERSONAWEAVER: Controllable Diversity Beyond Conventional Archetypes in Procedural Character Generation#1062516
Record · ID 1216962
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