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AI is dramatically lowering the cost of reading papers, writing code, and running experiments. But as research output explodes, telling which results can be trusted keeps getting harder. CiteArk connects the claims in scientific papers with their experimental conditions, execution process, result evidence, and verification records, so researchers and agents can verify claims, reuse experimental results, and build follow-up research on them instead of repeating work. We hope these trustworthy research records will grow into a scientific foundation that researchers, labs, and agents can all build on together.

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Decreasing the power-law exponent p makes the composed NTK spatially narrower and its Fourier spectrum broader with slower high-frequency falloff. · CiteArk

Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Not assessedPlan blockedFindingkernel-power-bandwidth

Decreasing the power-law exponent p makes the composed NTK spatially narrower and its Fourier spectrum broader with slower high-frequency falloff.

Source: paper:Figure 2(c,d), physical p. 5; §5 p. 5

Reported and observed measurements

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Assessments (0)

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Runs (0)

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Research Plan identity

Claim version: sha256:83731702ddbd79effe7c175877f775ab9d580f7d5356c426f66be77945fa886d
Planned experiments: 0
Evidence objects: 0

A concrete investigation is retained in kernel-structure, including necessary controls, scientific inputs, prospective observations and full finite quotes. Only the automatic qualitative verdict is blocked; this does not establish the route is operationally infeasible. Preserve evidence for independent assessment.

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