Paper Citation Record · LEDGER

Transformer Approximations from ReLUs

As of 7 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 1 inbound Pith citation observation for arXiv:2604.24878.

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

pith.paper-citation-record.v1
2604.24878 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-08T04:02:37.785615Z

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T05:08:00.711576Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T16:38:40.639612Z

Reference resolution

7 of 7 outbound references displayed

verified exact7
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d8c6bf73-e385-4d90-be7a-74d1243e8b43 · outbound

This paper cites Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory.

Transformer Approximations from ReLUs Unveil Conditional Diffusion Models with Classifier-free Guidance: A Sharp Statistical Theory

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:30.247996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 40da8e62-187c-4710-9db4-8d29428e96b5 · outbound

This paper cites Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency.

Transformer Approximations from ReLUs Fundamental Limits of Prompt Tuning Transformers: Universality, Capacity and Efficiency

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:30.210788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9522d1fd-1b49-4d0b-860c-5c4098e0af94 · outbound

This paper cites Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?.

Transformer Approximations from ReLUs Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:30.221196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e1af48db-cec8-4cc4-81c1-a229ba5be22f · outbound

This paper cites Transformers, parallel computation, and logarithmic depth.

Transformer Approximations from ReLUs Transformers, parallel computation, and logarithmic depth

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:30.235337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c9df388c-3704-4b9e-9efa-a3650ce10794 · outbound

This paper cites The Annals of Statistics 48(4):1875--1897, ://dx.doi.org/10.1214/19-AOS1875.

Transformer Approximations from ReLUs The Annals of Statistics 48(4):1875--1897, ://dx.doi.org/10.1214/19-AOS1875

Reference 5

Resolution: verified exact; doi, observed 2026-05-09T00:14:27.762690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9d46cfc0-234d-4293-8493-10aa6e9478d4 · outbound

This paper cites Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality.

Transformer Approximations from ReLUs Adaptivity of deep ReLU network for learning in Besov and mixed smooth Besov spaces: optimal rate and curse of dimensionality

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:30.252208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 0236d33b-d54c-485f-a33f-afd040ea0e27 · outbound

This paper cites The transformer cookbook.arXiv preprint arXiv:2510.00368.

Transformer Approximations from ReLUs The transformer cookbook.arXiv preprint arXiv:2510.00368

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:51:30.199583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

Observation f1d4879a-a851-498b-a8aa-0c87d41b0441 · inbound

Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model cites this paper.

Generalization Bounds for Transformer-Based Next-Token Prediction in a Language Model Transformer Approximations from ReLUs

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T16:38:40.640997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.