Decoding ML Decision: An Agentic Reasoning Framework for Large-Scale Ranking System 事件

Decoding ML Decision: An Agentic Reasoning Framework for Large-Scale Ranking System arXiv:2602.18640v2 Announce Type: replace Abstract: Modern large-scale ranking systems operate within a sophisticated landscape of competing objectives, operational constraints, and evolving product requirements. Progress in this domain is increasingly bottlenecked by the engineering context constraint: the arduous process of translating ambiguous product intent into reasonable, executable, verifiable hypotheses