3 papers
cs.AI2026
Choosing LLMs for Strategic Agent Interactions
Arastun Mammadli, Herbert Woisetschläger, Jawad Fayaz +1
Game-theoretic benchmarks claim that large language model (LLM) strategic decision-making varies across game types, interaction structures, and capability dimensions. However, they…
cs.LG2026
Cost-Optimal LLM Routing with Limited User Feedback under User Satisfaction Guarantees
Herbert Woisetschläger, Arastun Mammadli, Ryan Zhang +1
Inference costs for large language model (LLM) applications are rapidly growing, driven by surging demand and rising infrastructure cost. Users expect high-quality responses, and i…
cs.AI2026
AgentSearchBench: A Benchmark for AI Agent Search in the Wild
Bin Wu, Arastun Mammadli, Xiaoyu Zhang +1
The rapid growth of AI agent ecosystems is transforming how complex tasks are delegated and executed, creating a new challenge of identifying suitable agents for a given task. Unli…