Hierarchical LLM-based multi-agent systems can be optimized through specific routing strategies across different levels of data maturity.
Claims
Hierarchical LLM-based multi-agent systems can be optimized through specific routing strategies across different levels of data maturity.
Parent: Artificial IntelligenceEntity: Multi-Agent SystemsSub-entity: Agent Routing StrategiesImpact: positiveDate: Sep 25, 2026Target: Hierarchical LLM-based multi-agent systems
Source posts
Das Programm am letzten Tag der #SKILL2026
#Session7 – Softwaretechnik und Agenten
Philipp Julian Epple (Duale Hochschule Baden-Württemberg, DHBW Stuttgart). Agent Routing in Hierarchical LLM-Based Multi-Agent Systems: A Controlled Comparison of Five Routing Strategies Across Data Maturity
Sebastian Kirsch (Europäische Fernhochschule Hamburg, Euro-FH). Multi-Agent Orchestration Patterns for Enterprise Workflows: A Taxonomy and Design Framework
Helia Dadkhah (Freie Universität Berlin). The Role of the Software Engineer in Developing Software Using Coding Agents
Adam Kahirov (Duale Hochschule Baden-Württemberg, DHBW Stuttgart). How Much Does Calibration-Data Selection Matter for 4-bit GPTQ? A Statistical Parity Study of Text-Only Selection Across Three Model Families
Closing und #BestPaperAward
#Informatik26 #Informatik #TUDresden
0 boosts · 0 favs · 0 replies · Sep 25, 2026
#tudresden#informatik#informatik26#bestpaperaward#session7#skill2026
Der #BestPaperAward der #SKILL2026 geht dieses Jahr an Philipp Julian Epple von der Dualen Hochschule Baden-Württemberg, #DHBW Stuttgart für seinen Beitrag "Agent Routing in Hierarchical LLM-Based Multi-Agent Systems: A Controlled Comparison of Five Routing Strategies Across Data Maturity"
Herzlichen Glückwunsch!
#Informatik26 #Informatik #TUDresden
0 boosts · 0 favs · 0 replies · Sep 25, 2026
#tudresden#informatik#informatik26#dhbw#skill2026#bestpaperaward