Paper Citation Record · LEDGER

Inference for Regression with Variables Generated by AI or Machine Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2402.15585.

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

pith.paper-citation-record.v1
2402.15585 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:25:21.045567Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:17:29.316732Z

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 80c0e3da-9389-408e-beab-b67b906df3bf · inbound

A Deep Learning Approach to Heterogeneous Consumer Aesthetics in Fast Fashion cites this paper.

A Deep Learning Approach to Heterogeneous Consumer Aesthetics in Fast Fashion Inference for Regression with Variables Generated by AI or Machine Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-24T01:28:42.471853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation be79dd15-a58b-4076-ba7d-8b0ae0912402 · inbound

E-LDA: Toward Interpretable LDA Topic Models with Strong Guarantees in Logarithmic Parallel Time cites this paper.

E-LDA: Toward Interpretable LDA Topic Models with Strong Guarantees in Logarithmic Parallel Time Inference for Regression with Variables Generated by AI or Machine Learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T10:25:21.045567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 346e8be7-eb31-47b2-bff3-0bb3522a9ad6 · inbound

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Inference for Regression with Variables Generated by AI or Machine Learning

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-18T02:00:39.977214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1ae7e973-168c-4fa5-8b47-cebfed4fe402 · inbound

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach cites this paper.

Making Interpretable Discoveries from Unstructured Data: A High-Dimensional Multiple Hypothesis Testing Approach Inference for Regression with Variables Generated by AI or Machine Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T00:23:27.443178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb07f31c-2db3-47b2-a3cd-19dde1d8d4a0 · inbound

From Unstructured Data to Demand Counterfactuals: Theory and Practice cites this paper.

From Unstructured Data to Demand Counterfactuals: Theory and Practice Inference for Regression with Variables Generated by AI or Machine Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T11:45:38.974531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f7fbcf5-8676-4278-8731-e9f4c14e7917 · inbound

Bootstrapping with AI/ML-generated labels cites this paper.

Bootstrapping with AI/ML-generated labels Inference for Regression with Variables Generated by AI or Machine Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:31:17.361795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9d014eb0-545e-40c9-a92d-6833d6503e72 · inbound

Moment-Based Inference for Regression with Latent Dirichlet Covariates cites this paper.

Moment-Based Inference for Regression with Latent Dirichlet Covariates Inference for Regression with Variables Generated by AI or Machine Learning

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T20:22:37.149545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 10c2447a-368e-43c6-971b-f37c3b2cf4b1 · inbound

AI-Assisted Variance Reduction in Randomized Experiments cites this paper.

AI-Assisted Variance Reduction in Randomized Experiments Inference for Regression with Variables Generated by AI or Machine Learning

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-03T00:17:29.318154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.