AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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School of Artificial Intelligence and Data Science, University of Science and Technology of China
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It is found that several state-of-the-art deep-research agents on Deep Research Bench II satisfy fewer than 50% of the rubrics, revealing a substantial gap between current DRAs and human experts.
The results indicate that for precise, evidence-grounded questions over chat archives, much of the benefit credited to elaborate memory structures is recoverable by giving an agent controllable search over the unmodified record, with no LLM-based index construction at all.
This work introduces InMind, a 125-task, expert-verified benchmark spanning ten life domains, with 113 tasks grounded in citable public sources, and calls this failure mode the implicit-association blind spot, and introduces a minimal diagnostic probe that keeps memory visible before the query arrives recovers most of...
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