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arXiv Computation and Language By Yiling Wu (BridgeM, Inc.)

Representational Acquisition Under Bounded Resources

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The paper investigates how a learner’s need to keep acquired knowledge usable creates a trade‑off between storage and access costs, identifying precise endpoints that dictate different physical data organizations. For exact concept‑learning tasks, the authors derive a storage‑read curve within a constant factor, showing that one‑read compound queries require answer‑specific cells and incur exponentially costly updates, whereas one‑bit, order‑independent updates necessitate fact‑specific cells. The study further establishes robust bounds on expected distance from a coordinate encoding under uniform content distribution, limits the information inaccessible to a one‑read consumer, and explores how preservation constraints and distributed encodings affect update strategies, ultimately explaining how distinctions, uses, and update constraints jointly determine resource costs and organization.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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