Overview of the TREC 2025 Million Large Language Models track
Agentic AI envisions ecosystems of intelligent agents collaboratively solving complex tasks with minimal human intervention. In such ecosystems, each agent possesses specialized expertise, making effective expert selection central to overall system performance. While most current approaches assume a small number of well-documented models, real-world expertise is far more diverse and cannot be adequately captured through static metadata or hand-written descriptions. We anticipate a future with millions of specialized language models (LLMs), each excelling in different domains or problem types. Rather than relying on predefined capability statements, we propose a retrieval-based paradigm in...
| Authors | Evangelos Kanoulas, Panagiotis Eustratiadis, Jamie Callan et al. |
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| Primary category | cs.IR |
| Published | 25 September 2026 |
| Last updated at source | 25 September 2026 |
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