AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Evaluating user experience (UX) with automated computational methods has gained increasing attention, supported by empirical evidence from UXBench. However, binary preference prediction provides limited insight, while relying on a single user-agnostic reward model overlooks the inherent heterogeneity of users, whose ex...
The first user-centric benchmark grounded in real user feedback signals for evaluating preference alignment and dialogue generation is presented, demonstrating that user feedback prediction is a learnable capability and revealing different aspects that influence user experience.
This work formalizes this meta-capability as Delegation Intelligence in deep search and decomposes it into complementary dimensions-Search Decision-Making and Information Synthesis and Verification and develops a controllable synthesis pipeline built on document-grounded reverse engineering.
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