AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Through careful publication of AI-generated research papers, this work investigates how the scholarly ecosystem responds to AI authorship and discusses the implications of AI authorship on publishers, researchers, and the scientific system at large.
It is shown that the residual streams of language models under coding agents linearly encode properties of the evolving program: a logistic-regression probe on hidden states is able to decode whether the current code parses, passes its test suite, reduces the number of failing tests, and introduces regressions.
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