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Paper Citation Record · LEDGER

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis

As of 9 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2607.11591.

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

pith.paper-citation-record.v1
2607.11591 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T04:33:33.238860Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

21 of 21 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0019fc4b-1f9f-424d-bad8-e982e209da7b · outbound

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

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis NNGPT: Rethinking AutoML with large language models,

Reference 1

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Observation 95895342-3ef8-44d3-a4af-2fb08b3a08ae · outbound

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

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis LEMUR Neural Network Dataset: Towards Seamless AutoML

Reference 2

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Observation ba686e78-1743-48b7-afec-2479f5ed5706 · outbound

This paper cites LEMUR 2: Unlocking neural network diversity for AI,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis LEMUR 2: Unlocking neural network diversity for AI,

Reference 3

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Observation f78e194a-8ddc-4728-a67e-d12fa4e00312 · outbound

This paper cites Large Language Models as Optimizers.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Large Language Models as Optimizers

Reference 4

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Observation 99147c93-7f10-4d21-ab79-cc00a4198925 · outbound

This paper cites Mathematical discoveries from program search with large language models,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Mathematical discoveries from program search with large language models,

Reference 5

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:ca85ffb45b0f2d2c5cd96e557c1f8e4b7286c73e2d8674f81f7854f68d0df0cc

Observation 50e6bbfc-862c-48ea-a494-52f3f9469391 · outbound

This paper cites EvoPrompting: Language models for code-level neural architecture search,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis EvoPrompting: Language models for code-level neural architecture search,

Reference 6

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Observation 3da0a92a-fac6-4bf9-a22e-5c873ca2df89 · outbound

This paper cites ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution

Reference 7

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:4b233b89f7ee556e05ec5a518e94cd8a11e1326adde4ea86dce0fe28b009c8f5

Observation 949165bf-a787-4afa-a8ed-ee76d4925dee · outbound

This paper cites LLMatic: Neural architecture search via large language models and quality-diversity optimization,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis LLMatic: Neural architecture search via large language models and quality-diversity optimization,

Reference 8

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:b0f3a10e4df68f64759dea92e2e75fe7ef153512f50ca09b404b60c0a2edb337

Observation e97917f3-8977-4726-8023-3c35fbd25f5a · outbound

This paper cites Simon algorithm in measurement-based quantum computing.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Simon algorithm in measurement-based quantum computing

Reference 9

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:21e2ad130c842c65db6a2b760efffa3ca6611ae3923d7e39ac85f18d913b883b

Observation 1eb247b1-1731-4399-bcc3-c979cb1ed5f0 · outbound

This paper cites Curriculum learning,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Curriculum learning,

Reference 10

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:e3c4c0e5e5822fd13b8ca527b71ed0101239f6a3c5941adaa5221451e6b3d1aa

Observation a3a85c45-cbcf-4f82-b646-be5d445f1b5c · outbound

This paper cites Self-paced learning for latent variable models,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Self-paced learning for latent variable models,

Reference 11

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:b2fb88fc7f8ab0a890da44eb27dc73cc3887fbd6b85acfc0abcf6b857f85a3c1

Observation 356f5925-4ef1-4e47-ac6c-654974536891 · outbound

This paper cites Automated curriculum learn- ing for neural networks,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Automated curriculum learn- ing for neural networks,

Reference 12

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Observation b0720080-a4e3-42c0-bd81-a1d5f6b4fcf5 · outbound

This paper cites On the power of curriculum learning in training deep networks,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis On the power of curriculum learning in training deep networks,

Reference 13

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:d372866a906af39bf50e74aae7219dc1695c55d0c97127718b19cfa7b17c2ae5

Observation 5b507d54-dccd-4dda-be20-d16f9b34ba1e · outbound

This paper cites On the resemblance and containment of documents,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis On the resemblance and containment of documents,

Reference 14

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Observation 614a81f0-79d6-4846-905f-52f0b5af547a · outbound

This paper cites A novel neural source code representation based on abstract syntax tree,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis A novel neural source code representation based on abstract syntax tree,

Reference 15

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:79f98e200c1cf67bc7648b03e995a65c10c69783e3f763a7ab6b2951064f746c

Observation 903bf409-08b8-4860-b174-eb117364e6db · outbound

This paper cites CodeBERT: A pre-trained model for programming and natural languages,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis CodeBERT: A pre-trained model for programming and natural languages,

Reference 16

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:8d455b029ea4a1c0fe19f8b32987b4702eb71fd27398ff6bf06a41483caeaedb

Observation 9d13064e-d408-4659-ad7a-5bb175a380f5 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:d1234ef71100a1dbb80b518741a635092501d96e1797845ad17493de7568cbd5

Observation f91acb81-f334-4657-aaa8-d005ad265d0d · outbound

This paper cites Editing models with task arithmetic,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Editing models with task arithmetic,

Reference 18

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:77b25531671831bdea7066e9179cccae006505a5fb855a0f592d5e4894a2847a

Observation 6e1767b9-8733-4d48-81be-bf7be01bec16 · outbound

This paper cites TIES-merging: Resolving interference when merging models,.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis TIES-merging: Resolving interference when merging models,

Reference 19

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source=pdf_text observed=2026-07-14T04:33:33.238860Z digest=sha256:70bcc4d280821c4460ad3ca787fb9cc6b86adb0a29ca935eed5e3b616109ba80

Observation 3e33077c-cdfe-4e4c-a17a-4cfbfdb668b6 · outbound

This paper cites Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch

Reference 20

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Observation 82d54b3b-3c1e-4136-a87e-4bd60452d789 · outbound

This paper cites UPME: An Unsupervised Peer Review Framework for Multimodal Large Language Model Evaluation.

Similarity-Guided Curriculum Fine-Tuning of LLMs for Neural Architecture Synthesis UPME: An Unsupervised Peer Review Framework for Multimodal Large Language Model Evaluation

Reference 21

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Pith citing papers

No inbound Pith citation observations are available.