发表机构
NeverBlink; Rijksuniversiteit Groningen（NeverBlink; 格罗宁根大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文指出按接收者类型划分编解码设计具有误导性，码率取决于任务范围，并扩展源编码至有限任务族，证明任务扩大时源与分裂特征编码码率不再相等。
AI 中文摘要
我们认为，将编解码器设计划分为“面向机器的编码”（Coding for Machines, CfM）和“面向人类的编码”（Coding for Humans, CfH）是一种误导性的区分，因为它不能决定编解码器可以丢弃哪些信息。接收者的身份并不决定可允许的信息损失。所需的码率取决于任务范围，包括要支持的预测、其损失和可容忍的风险、编码器的观测以及允许的解码过程。值得注意的是，机器任务的最低码率可能高于受限的人类决策。在选定机器任务上的码率节省仅适用于所述要求，而非按接收者类型的内在排序。我们将源编码和特征编码扩展到有限任务族，推导了何时限制编码器观测能保持最低码率，并表明随着任务范围的扩大，源编码与分裂特征编码码率之间的相等性不再成立。
英文摘要
We argue that dividing codec design into Coding for Machines (CfM) and Coding for Humans (CfH) is a misleading distinction for deciding what information a codec may discard. Receiver identity does not determine admissible information loss. The required rate depends on task scope, including the predictions to support, their losses and tolerated risks, the encoder observation, and the permitted decoding procedures. Notably, a machine task may have a higher minimum rate than a restricted human decision. Rate savings on selected machine tasks apply only to the stated requirements, not to an intrinsic ordering by receiver type. We extend source and feature coding to finite task families, derive when restricting the encoder observation preserves the minimum rate, and show that equality between source and split-feature coding rates can no longer hold as the task scope expands.
