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Paper Citation Record · LEDGER

GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2305.05351.

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

pith.paper-citation-record.v1
2305.05351 v4

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 2026-08-22T06:32:14.747728+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:23:42.509032Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T14:38:00.540914Z

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 12c8346f-0e65-4df5-ab5f-90c575472cc1 · inbound

PINNsAgent: Automated PDE Surrogation with Large Language Models cites this paper.

PINNsAgent: Automated PDE Surrogation with Large Language Models GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T17:38:24.741597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:38:24.741597Z digest=sha256:0e11eb936da4499ccb45477535d657be84423c9f894843e1f1125eca5e2f4c7e

Observation 9245ab6b-e796-4a4a-a94a-ee80c7158774 · inbound

Transferrable Surrogates in Expressive Neural Architecture Search Spaces cites this paper.

Transferrable Surrogates in Expressive Neural Architecture Search Spaces GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T12:23:42.509032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:23:42.509032Z digest=sha256:2fce154dff4949a05dc932301ec3dbb0f116bff692cef98933a44b306ff38e67

Observation aac6f93e-4459-4da3-b0f3-a56517cdcf2b · inbound

Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications cites this paper.

Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T15:14:09.886146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:14:09.886146Z digest=sha256:2ade55edccd117a551059afcbd215a95bf0b7f424a5cbf2698a46d25bd857475

Observation d4cd9355-beba-45f3-8410-618aec5666f1 · inbound

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving cites this paper.

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

Reference 126

Resolution
unresolved
no resolver link, observed 2026-08-04T20:55:41.586340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:55:41.586340Z digest=sha256:b5c246cf0d69ae0853c881b664cecbebf0c9c20c955b9fcced08b6344d73e95f

Observation 84d75f2e-39d3-4ab7-a5e9-50486006be92 · inbound

Closed-Loop LLM Discovery of Non-Standard Channel Priors in Vision Models cites this paper.

Closed-Loop LLM Discovery of Non-Standard Channel Priors in Vision Models GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-16T14:38:00.543071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-16T14:34:24.849584Z digest=sha256:49a7ac7f78a3cbced567ac41bb6541a53e38ac3f4a7a81f76e3a2fce7a39b5d9

Observation ca338cd0-7916-472c-917d-eb1d74ad6b7f · inbound

LLM-Driven AutoML for Cross-Lingual Handwritten OCR: Closed-Loop Neural Architecture Search with GPT-5, GPT-4o, and Claude Sonnet 4 cites this paper.

LLM-Driven AutoML for Cross-Lingual Handwritten OCR: Closed-Loop Neural Architecture Search with GPT-5, GPT-4o, and Claude Sonnet 4 GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-01T23:09:34.915773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T23:09:34.915773Z digest=sha256:eedb7103a66da1533ba49dfcc9c8c8dd3990696804decd9dd2e38074e2e444b8

Observation 2771565b-bd81-4c2b-a4c8-995323be6151 · inbound

Scaling Closed-Loop Feature Channel Configuration with LLMs cites this paper.

Scaling Closed-Loop Feature Channel Configuration with LLMs GPT-NAS: Evolutionary Neural Architecture Search with the Generative Pre-Trained Model

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T08:13:04.761560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:13:04.761560Z digest=sha256:03e66f00871fbb1bd3277aa73a2eb980f746cb033d78451c08a851f8e896ac18