arXiv:2606.04308v1 Announce Type: new Abstract: Reading augmentation systems increasingly help readers process text at scale. While these tools address real constraints of time and cognitive load, they often implicitly frame reading as information transmission, or "reading to discard," delegating interpretation and effort to the machine. Yet this delegation changes the outcome of reading. For example, in scholarly reading, deciding what a research text implies and why it matters is central to th
This paper provides a strong contrarian perspective against the current LLM trend of efficiency-focused summarization. It offers high novelty by framing reading as a creative act rather than information retrieval, signaling a shift in how AI agents might support scholarly work.