Competence-aware orchestration adjusts communication in agent teams
The framework changes agent roles and communication patterns according to task-specific capabilities.
Event / data period: 2026-10-09
Published: · Updated:
Researchers at The Hong Kong Polytechnic University presented a framework for competence-aware agent coordination. It compares task context with each model’s capability profile and adjusts role assignments and the communication graph, aiming to avoid a fixed multi-agent arrangement for every task.
Across the benchmarks, the authors report a 36.26% reduction in token use while maintaining average scores in selected strong-model configurations. The result is tied to GPT-4o-based evaluations and specified benchmark tasks; the paper does not show that capability profiles can be inferred with the same accuracy for other models or real workflows.
Data
Research result
Six benchmarks; GPT-4o-based experiments; average token use in selected configurations
| Token-use reduction in selected strong-model configurations | 36.26 | Six benchmarks; GPT-4o-based experiments; average token use in selected configurations |
Methodology
The value is limited to the benchmark experiment reported in the paper; it is not a field result or general performance guarantee.
Updated:
Subjects and places
Subject proposals
- Science and technologySuggested
- Preserved editorial category/topic; broad candidate onlyarxiv.org ↗
Geographic references
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- Hong Kong SAR China · Place role: Coverage · Place type: Country or area · Location precision: RegionalEvidence
- Explicit preserved editorial country/region; no city or national centroid inferredarxiv.org ↗