AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Large language model (LLM) evaluators are increasingly used to assess personalized assistants, yet whether they can reliably judge personalization has rarely been tested. We introduce PersEvalBench, a benchmark testing whether an evaluator can recognize appropriate and inappropriate uses of user history. It contains 40...
Belief-Calibrated Optimization is introduced, a method that writes that belief down as a persistent in-context document and continually revises that document as new candidates are evaluated, and reaches a higher train passrate than a matched control that lacks only the world model.
Hear2Act is introduced, a unified evaluation protocol for text and spoken assistants with 480 persona-grounded scenarios, hidden user concerns, and objectively verifiable outcomes that show that prosody matters when lexical evidence is insufficient, and that audio-capable LLMs can recover information from speech but do...
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