AI RESEARCH

Support Sufficiency as Consequence-Sensitive Compression in Belief Arbitration

arXiv CS.LG

ArXi:2604.16434v1 Announce Type: cross When a system commits to a hypothesis, much of the evidential structure behind that commitment is lost to compression. Standard accounts assume that selected content and scalar confidence suffice for downstream control. This paper argues that they do not, and that determining what must survive compression is itself a consequence-sensitive problem. We develop a recurrent arbitration architecture in which active constraint fields jointly determine a hypothesis geometry over candidates.