Paper Citation Record · LEDGER

A Theory of Usable Information Under Computational Constraints

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2002.10689.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2002.10689 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:56:33.668306Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-25T05:10:21.948130Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d07b51e3-2ee7-4781-862f-836a8a02fad1 · inbound

One-shot Federated Learning via Synthetic Distiller-Distillate Communication cites this paper.

One-shot Federated Learning via Synthetic Distiller-Distillate Communication A Theory of Usable Information Under Computational Constraints

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T20:56:33.668306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1557a7cb-8939-4676-8e91-3d26f9c25a62 · inbound

Laplace Sample Information: Data Informativeness Through a Bayesian Lens cites this paper.

Laplace Sample Information: Data Informativeness Through a Bayesian Lens A Theory of Usable Information Under Computational Constraints

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T15:26:09.945249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47911f31-5f6f-4971-b1a1-c16b5621bfa8 · inbound

How much do language models memorize? cites this paper.

How much do language models memorize? A Theory of Usable Information Under Computational Constraints

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:41.368427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccc34d92-69f0-4757-ae50-eb8e762be252 · inbound

Aligning Multimodal Representations through an Information Bottleneck cites this paper.

Aligning Multimodal Representations through an Information Bottleneck A Theory of Usable Information Under Computational Constraints

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T10:43:53.975431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 758f968f-13d4-4e3b-bcb8-88eb9031e3b4 · inbound

Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs cites this paper.

Hessian-Enhanced Token Attribution (HETA): Interpreting Autoregressive LLMs A Theory of Usable Information Under Computational Constraints

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:41:02.188710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 60e19352-28ee-41ec-a964-f5c94f9d4f84 · inbound

Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting cites this paper.

Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting A Theory of Usable Information Under Computational Constraints

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:10:21.950819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 24557a6d-177f-462f-b870-b310d96bb688 · inbound

Are We Ready for AI-Driven Discovery? AI Verification Before the Next Fundamental Physics Breakthrough cites this paper.

Are We Ready for AI-Driven Discovery? AI Verification Before the Next Fundamental Physics Breakthrough A Theory of Usable Information Under Computational Constraints

Reference 82

Resolution: unresolved; no resolver link, observed 2026-07-14T00:50:24.285797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.