7 papers
Organizing, Orchestrating, and Benchmarking Agent Skills at Ecosystem Scale
Hao Li, Chunjiang Mu, Jianhao Chen +5
The rapid proliferation of Claude agent skills has raised the central question of how to effectively leverage, manage, and scale the agent skill ecosystem. In this paper, we propos…
ICL-Router: In-Context Learned Model Representations for LLM Routing
Chenxu Wang, Hao Li, Yiqun Zhang +6
Large language models (LLMs) often exhibit complementary strengths. Model routing harnesses these strengths by dynamically directing each query to the most suitable model, given a…
Beyond GPT-5: Making LLMs Cheaper and Better via Performance-Efficiency Optimized Routing
Yiqun Zhang, Hao Li, Jianhao Chen +4
Balancing performance and efficiency is a central challenge in large language model (LLM) advancement. GPT-5 addresses this with test-time routing, dynamically assigning queries to…
Learning Compact Representations of LLM Abilities via Item Response Theory
Jianhao Chen, Chenxu Wang, Gengrui Zhang +5
Recent years have witnessed a surge in the number of large language models (LLMs), yet efficiently managing and utilizing these vast resources remains a significant challenge. In t…
Conflict Detection for Temporal Knowledge Graphs:A Fast Constraint Mining Algorithm and New Benchmarks
Jianhao Chen, Junyang Ren, Wentao Ding +3
Temporal facts, which are used to describe events that occur during specific time periods, have become a topic of increased interest in the field of knowledge graph (KG) research.…
Stop Overvaluing Multi-Agent Debate -- We Must Rethink Evaluation and Embrace Model Heterogeneity
Hangfan Zhang, Zhiyao Cui, Jianhao Chen +5
Multi-agent debate (MAD) has gained significant attention as a promising line of research to improve the factual accuracy and reasoning capabilities of large language models (LLMs)…