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Paper Citation Record · LEDGER

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation

As of 10 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.05704.

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

pith.paper-citation-record.v1
2607.05704 v1

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T03:26:40.346199Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

  • verified exact6
  • verified fuzzy14
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8337e21f-2ffe-421a-a197-d788f2c87dcf · outbound

This paper cites Optuna: A next-generation hyperparameter optimization framework.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Optuna: A next-generation hyperparameter optimization framework

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.586898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation 772b0d9e-5750-4cc1-b4fd-244ad9239900 · outbound

This paper cites Bergstra, Remi Bardenet, Yoshua Bengio, and Bal- azs Kegl.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Bergstra, Remi Bardenet, Yoshua Bengio, and Bal- azs Kegl

Reference 2

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verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.189037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:069726b46309ab25b4577f71a5fc8002708afc118de4bec800c11c03340d050c

Observation da54b1d6-fdc9-4b43-a654-da2dd91ceac2 · outbound

This paper cites an unresolved cited work.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Unresolved cited work

Reference 3

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unresolved
raw_fallback, observed 2026-07-11T03:27:47.513505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Observation de26e055-e4ae-4695-a5e5-7458375a678a · outbound

This paper cites Evaluating Large Language Models Trained on Code.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Evaluating Large Language Models Trained on Code

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-07-11T03:27:45.360441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:5bf236b9285ff2f21905e28230b9ffbcd4cd655261dc1dbf5f17f50a4b11eab1

Observation 0c61486a-20db-4b8d-a303-4e51df28cf5c · outbound

This paper cites Enhancing LLM-based neural network generation: Few-shot prompting and efficient vali- dation for automated architecture design.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Enhancing LLM-based neural network generation: Few-shot prompting and efficient vali- dation for automated architecture design

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.464142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:5d361af4cb0a353adb9dbc9e45193c812b3fe716a12b6642ece4c581c2bb1802

Observation 4e489e89-398a-4440-820d-f63f5107097f · outbound

This paper cites Neural architecture search: A survey.Journal of Machine Learning Research, 20(55):1–21.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Neural architecture search: A survey.Journal of Machine Learning Research, 20(55):1–21

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.162423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:3ee68596d738aa9c9760093e0757b36d4b5aaf7b045e76a9129bf9a0dcd3e101

Observation f6a41cae-0a01-4dc4-8070-76deda681eec · outbound

This paper cites LEMUR Neural Network Dataset: Towards Seamless AutoML.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation LEMUR Neural Network Dataset: Towards Seamless AutoML

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-11T03:27:45.300357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:c643204ef47687d85b074b1594eb72d6e1b94f16dbcf9164507c239fdf97b049

Observation bc7665d2-23ae-4d99-baca-418d0349938b · outbound

This paper cites Resource- efficient iterative LLM-based NAS with feedback memory.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Resource- efficient iterative LLM-based NAS with feedback memory

Reference 8

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verified exact
arxiv_id, observed 2026-07-11T03:27:45.419024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:66fb7c96a8d0f040b8a80e89cc77af0dc41c6a790d800b13f8fc915cae3d5294

Observation c2933c68-8ce7-48f6-80fe-a0915de403b6 · outbound

This paper cites EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-07-11T03:27:45.475083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:d0455f36907fa87ebb566d5fd80205d5cc0331afc3d05e1615f524a136938726

Observation b07c5111-e0c0-4e55-86e8-787365e9756e · outbound

This paper cites an unresolved cited work.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Unresolved cited work

Reference 10

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unresolved
raw_fallback, observed 2026-07-11T03:27:47.327922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:4eba01a97468027da316c2e8fb47ed325e9f77b571fa68a4a8ecdc3efefbc56c

Observation b9054a29-d78c-46bd-b850-6a11a69be9ee · outbound

This paper cites NNGPT: Rethinking AutoML with large language models.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation NNGPT: Rethinking AutoML with large language models

Reference 11

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verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.242165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:c63b0a559c5e7bb8726fc8b6d7be0db9e63bf5ad59f8800737b1599793190db4

Observation 85ae9f2f-3a4e-4278-8e68-d978703ea272 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Retrieval-augmented generation for knowledge-intensive NLP tasks

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.270080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:d08ed4d3b63ef2a079172e2561461c6885919e4c47a25ecc01ab0e69b7739722

Observation 830645c0-9ae9-4cb7-977c-34774aa9c237 · outbound

This paper cites Hyperband: A novel bandit-based approach to hyperparameter optimization.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Hyperband: A novel bandit-based approach to hyperparameter optimization

Reference 13

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verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.212925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:a3eeae7b0104272fe7c95b6e5d0d9edff603e3e8b63beb0ae9e43c26f814509f

Observation 3f47ed42-1d41-41d5-aff1-37b085fc62da · outbound

This paper cites Competition- level code generation with AlphaCode.Science, 378(6624): 1092–1097, 2022.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Competition- level code generation with AlphaCode.Science, 378(6624): 1092–1097, 2022

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.488788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:dc652314dad71471664c40e8c0308eaab20ecba85bace836bf49a6dfee477325

Observation 17b6503a-32f6-4919-9e08-a39b940d428e · outbound

This paper cites Best practices for scien- tific research on neural architecture search.Journal of Ma- chine Learning Research, 21(243):1–18, 2020.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Best practices for scien- tific research on neural architecture search.Journal of Ma- chine Learning Research, 21(243):1–18, 2020

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.302109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:6bf140c5f04035931fddd3d286abe2fa103c3f03957ae2775925a71858473588

Observation 04ed7470-cf09-4580-88a7-576b4c5e1575 · outbound

This paper cites DARTS: Differentiable architecture search.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation DARTS: Differentiable architecture search

Reference 16

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verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.414123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:c26b3b501f7e366314ea0a3b63489be5350655130b94e86fef52a47ae0cb2b45

Observation ec011453-5fc6-46d1-94a1-c7036580381a · outbound

This paper cites Self-refine: Iterative refinement with self-feedback.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Self-refine: Iterative refinement with self-feedback

Reference 17

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verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.441414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:c3c59fbdb24fb528815d6071a0f946609756b193ed4eb88f54f769707483f15a

Observation 71297b83-f788-42ea-bb3c-f3c0ef461db1 · outbound

This paper cites LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization

Reference 18

Resolution
metadata mismatch
local_arxiv, observed 2026-07-11T03:27:45.389189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:76f0ebbfa85825acf7dde8e480d47646ebc8f54579c750f8e8d1678d11fe4796

Observation 61feee89-ac3f-4901-8b6a-5a4641dbb144 · outbound

This paper cites an unresolved cited work.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-07-11T03:27:47.539583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:08a605866d481026d564b7a9d1960faede827fe3fa18b3086267ff16ed680069

Observation 1c71f440-f1d4-46b1-8f5c-172495180db8 · outbound

This paper cites AutoML-Zero: Evolving Machine Learning Algorithms From Scratch.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation AutoML-Zero: Evolving Machine Learning Algorithms From Scratch

Reference 20

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verified exact
local_arxiv, observed 2026-07-11T03:27:45.326886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:548fc2d4c7171ebed44420efbec652dc9e636fdf2ddcbfd2fe032bfe1b8f5660

Observation 5420d4a6-e44e-4abb-94de-af1cbb9dbb83 · outbound

This paper cites Reflex- ion: Language agents with verbal reinforcement learning.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Reflex- ion: Language agents with verbal reinforcement learning

Reference 21

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raw_fallback, observed 2026-07-11T03:27:47.136367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:53f7165e82942ab37b415f4833f5bea31ec0d63e79ac8f8d2c17e44f41f87165

Observation ea3bc1ab-df1e-4b1f-bec4-eeec2057f4d8 · outbound

This paper cites an unresolved cited work.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Unresolved cited work

Reference 22

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unresolved
raw_fallback, observed 2026-07-11T03:27:47.358211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:723a3e3cb35fdd71dfda9a0ebdafd06b54aeb2ce964fe4f456baec419ccc51c6

Observation ed1dfcc2-43df-4dad-871a-9c866acc02c1 · outbound

This paper cites LEMUR 2: Unlocking neural net- work diversity for AI.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation LEMUR 2: Unlocking neural net- work diversity for AI

Reference 23

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verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.386813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:9a2293edaef7c784e1d125ee48513f1c7554c1ea0c5b3c3d44e4a8c08d3fa183

Observation bc372f1f-63c7-44f7-b057-1f697bb237ff · outbound

This paper cites Large Language Models as Optimizers.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Large Language Models as Optimizers

Reference 24

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metadata mismatch
local_arxiv, observed 2026-07-11T03:27:45.500929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:f49c5046b11b6ecba2f3e4cc306cb6989edceed2dfc4b3b8ebd63a99d4bb4837

Observation 8dd83006-649e-469d-97d3-9b9c185661ba · outbound

This paper cites ReAct: Synergizing reasoning and acting in language models.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation ReAct: Synergizing reasoning and acting in language models

Reference 25

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verified fuzzy
raw_fallback, observed 2026-07-11T03:27:47.562712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:cf6a5808d1b14d0037f86382d63245728c00f0f5205132e466281387fd0941e1

Observation db809426-3d31-403b-86c6-3550c9349f4c · outbound

This paper cites Neural Architecture Search with Reinforcement Learning.

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation Neural Architecture Search with Reinforcement Learning

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-07-11T03:27:45.445234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T03:26:40.346199Z digest=sha256:f5b7e443bcfdb3e41d3a4b5f38842b1f91f28734540fe34a3c539531ce2c18e7

Pith citing papers

No inbound Pith citation observations are available.