Paper Citation Record · LEDGER

GLM Inference with AI-Generated Synthetic Data Using Misspecified Linear Regression

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2503.21968.

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

pith.paper-citation-record.v1
2503.21968 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T15:21:56.103111Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T21:10:09.189597Z

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 a3f48304-eb05-4411-88e9-ca84d9f86595 · inbound

General Synthetic-Powered Inference cites this paper.

General Synthetic-Powered Inference GLM Inference with AI-Generated Synthetic Data Using Misspecified Linear Regression

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T15:21:56.103111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbc1a147-c355-4e78-b98f-855c76168e50 · inbound

High-Dimensional Statistics: Reflections on Progress and Open Problems cites this paper.

High-Dimensional Statistics: Reflections on Progress and Open Problems GLM Inference with AI-Generated Synthetic Data Using Misspecified Linear Regression

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:36:06.694920Z

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 5053560d-c836-47c0-82d2-ef9743351f9b · inbound

High-Dimensional Statistics: Reflections on Progress and Open Problems cites this paper.

High-Dimensional Statistics: Reflections on Progress and Open Problems GLM Inference with AI-Generated Synthetic Data Using Misspecified Linear Regression

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-01T13:15:45.954016Z

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 903585e6-ac6c-4831-a8c1-05242c550ef7 · inbound

Valid Inference with Synthetic Data via Task Exchangeability cites this paper.

Valid Inference with Synthetic Data via Task Exchangeability GLM Inference with AI-Generated Synthetic Data Using Misspecified Linear Regression

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T16:28:39.060469Z

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 ba47d74e-6fb2-4df5-9e73-9979a82b8c31 · inbound

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification? cites this paper.

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification? GLM Inference with AI-Generated Synthetic Data Using Misspecified Linear Regression

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T21:10:09.192278Z

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.