Paper Citation Record · LEDGER

Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2310.12462.

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

pith.paper-citation-record.v1
2310.12462 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:11:39.392118Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T18:00:50.338952Z

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 92718ebd-bee0-4724-a5ae-f894fd45279e · inbound

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models cites this paper.

H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights

Reference 116

Resolution: verified exact; arxiv_id, observed 2026-05-17T18:00:50.341337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7438ad60-30a7-4d3d-a21b-8e8a19428365 · inbound

Numerical Pruning for Efficient Autoregressive Models cites this paper.

Numerical Pruning for Efficient Autoregressive Models Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:26.935672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91dfeeb0-775c-4f0f-a5de-dec1e9286310 · inbound

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers cites this paper.

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T14:11:39.392118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a9c632-0286-431e-b53e-3875e65c56c5 · inbound

Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation cites this paper.

Video Latent Flow Matching: Optimal Polynomial Projections for Video Interpolation and Extrapolation Unmasking Transformers: A Theoretical Approach to Data Recovery via Attention Weights

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T18:51:12.389438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.