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Paper Citation Record · LEDGER

Loss Functions for Predictor-based Neural Architecture Search

As of 12 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2506.05869.

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

pith.paper-citation-record.v1
2506.05869 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:20:34.584120Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

45 of 45 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 39ff36cf-7357-4cb7-b9d1-3025d1016751 · outbound

This paper cites Zero-Cost Proxies for Lightweight NAS.

Loss Functions for Predictor-based Neural Architecture Search Zero-Cost Proxies for Lightweight NAS

Reference 1

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Observation 809b1e8e-d131-4e25-93d8-dc6763f72a8e · outbound

This paper cites Once-for-All: Train One Network and Specialize it for Efficient Deployment.

Loss Functions for Predictor-based Neural Architecture Search Once-for-All: Train One Network and Specialize it for Efficient Deployment

Reference 2

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Observation 38c3ad30-9941-40e0-88dd-8dc6c4347728 · outbound

This paper cites Nas-bench-201: Extending the scope of reproducible neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Nas-bench-201: Extending the scope of reproducible neural architecture search

Reference 3

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Observation 60d04158-ccea-4928-bcb0-626f198ba04b · outbound

This paper cites Transnas-bench-101: Improving transferability and generalizability of cross-task neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Transnas-bench-101: Improving transferability and generalizability of cross-task neural architecture search

Reference 4

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Observation 8ef92784-4b29-40ef-b104-e487e9311603 · outbound

This paper cites Brp-nas: Prediction-based nas using gcns.Proc.

Loss Functions for Predictor-based Neural Architecture Search Brp-nas: Prediction-based nas using gcns.Proc

Reference 5

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Observation 12742a03-d689-49da-ad59-d45b999cd3d3 · outbound

This paper cites Neural architecture search: A survey.The Journal of Ma- chine Learning Research, 20(1):1997–2017, 2019.

Loss Functions for Predictor-based Neural Architecture Search Neural architecture search: A survey.The Journal of Ma- chine Learning Research, 20(1):1997–2017, 2019

Reference 6

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Observation 83512ff6-e39e-472d-8d0b-49bf37ca4579 · outbound

This paper cites Bohb: Ro- bust and efficient hyperparameter optimization at scale.

Loss Functions for Predictor-based Neural Architecture Search Bohb: Ro- bust and efficient hyperparameter optimization at scale

Reference 7

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Source-reported events for the cited work

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Observation edc78d4d-9a98-42f0-9d82-5bbf0b3eadb1 · outbound

This paper cites Nas-fpn: Learning scalable feature pyramid architecture for object de- tection.

Loss Functions for Predictor-based Neural Architecture Search Nas-fpn: Learning scalable feature pyramid architecture for object de- tection

Reference 8

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Source-reported events for the cited work

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Observation 07ca160f-d92e-428c-a797-819ee79f0a49 · outbound

This paper cites Arch-graph: Acyclic architecture relation predictor for task-transferable neural ar- chitecture search.

Loss Functions for Predictor-based Neural Architecture Search Arch-graph: Acyclic architecture relation predictor for task-transferable neural ar- chitecture search

Reference 9

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Source-reported events for the cited work

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Observation 87578b4e-5b54-45e6-8d6e-c2ed9e4bf6e9 · outbound

This paper cites Flowerformer: Empowering neural architecture encod- ing using a flow-aware graph transformer.

Loss Functions for Predictor-based Neural Architecture Search Flowerformer: Empowering neural architecture encod- ing using a flow-aware graph transformer

Reference 10

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Observation dc84cdbe-c85f-4cbf-8b6e-b2d2d69247fb · outbound

This paper cites On optimizing top-k metrics for neu- ral ranking models.

Loss Functions for Predictor-based Neural Architecture Search On optimizing top-k metrics for neu- ral ranking models

Reference 11

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Observation 5026f298-b897-4640-bf8b-dbe548e5d5ae · outbound

This paper cites Graph masked au- toencoder enhanced predictor for neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Graph masked au- toencoder enhanced predictor for neural architecture search

Reference 12

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Observation 85e63489-069d-48f7-99b8-9c57187da83b · outbound

This paper cites Neural architec- ture search with bayesian optimisation and optimal transport.

Loss Functions for Predictor-based Neural Architecture Search Neural architec- ture search with bayesian optimisation and optimal transport

Reference 13

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Observation 931debfa-ca7b-4967-8737-e0f61293fd16 · outbound

This paper cites A new measure of rank correlation.

Loss Functions for Predictor-based Neural Architecture Search A new measure of rank correlation

Reference 14

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Source-reported events for the cited work

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Observation c9b3b58d-b24c-450b-b5f4-192a08e4a72b · outbound

This paper cites Semi-supervised classifi- cation with graph convolutional networks.

Loss Functions for Predictor-based Neural Architecture Search Semi-supervised classifi- cation with graph convolutional networks

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 42793af0-a4dd-4196-81d5-3e4b8d425002 · outbound

This paper cites Learning multiple layers of features from tiny images.

Loss Functions for Predictor-based Neural Architecture Search Learning multiple layers of features from tiny images

Reference 16

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Source-reported events for the cited work

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Observation 8fe88647-de07-4c4e-b053-4ad7c0340831 · outbound

This paper cites Progressive neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Progressive neural architecture search

Reference 17

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Source-reported events for the cited work

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Observation 960fc862-491b-40cf-88e5-5fdc3b1ca58c · outbound

This paper cites Darts: Differentiable architecture search.

Loss Functions for Predictor-based Neural Architecture Search Darts: Differentiable architecture search

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c24a6093-64aa-4f75-ac8c-c16393022a1c · outbound

This paper cites Homogeneous architecture augmentation for neural predictor.

Loss Functions for Predictor-based Neural Architecture Search Homogeneous architecture augmentation for neural predictor

Reference 19

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Source-reported events for the cited work

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Observation 8ba6c0ee-e0b5-4f84-a3bb-c8266cc897ad · outbound

This paper cites Bridge the gap between architecture spaces via a cross-domain predictor.Proc.

Loss Functions for Predictor-based Neural Architecture Search Bridge the gap between architecture spaces via a cross-domain predictor.Proc

Reference 20

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Observation 16fb8a12-0450-4512-9722-7ebc5047c0a7 · outbound

This paper cites Tnasp: A transformer-based nas predictor with a self- evolution framework.Proc.

Loss Functions for Predictor-based Neural Architecture Search Tnasp: A transformer-based nas predictor with a self- evolution framework.Proc

Reference 21

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Observation b5187dc2-50a7-431d-b699-5b3b222d4672 · outbound

This paper cites Pinat: A permutation invari- ance augmented transformer for nas predictor.

Loss Functions for Predictor-based Neural Architecture Search Pinat: A permutation invari- ance augmented transformer for nas predictor

Reference 22

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Source-reported events for the cited work

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Observation a827d943-151f-46d9-a45f-81c2f8c73865 · outbound

This paper cites Neural architecture optimization.Proc.

Loss Functions for Predictor-based Neural Architecture Search Neural architecture optimization.Proc

Reference 23

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Source-reported events for the cited work

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Observation 70e8e6bf-8604-425e-8147-965443a815ea · outbound

This paper cites A generic graph-based neural architecture encoding scheme for predictor-based nas.

Loss Functions for Predictor-based Neural Architecture Search A generic graph-based neural architecture encoding scheme for predictor-based nas

Reference 24

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Source-reported events for the cited work

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Observation c01b157c-0e25-4b64-a07a-6223ace8ea05 · outbound

This paper cites Evaluating ef- ficient performance estimators of neural architectures.Proc.

Loss Functions for Predictor-based Neural Architecture Search Evaluating ef- ficient performance estimators of neural architectures.Proc

Reference 25

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Observation 362f1b05-182f-4c2f-bd72-052d9cab0252 · outbound

This paper cites Ta-gates: An encoding scheme for neu- ral network architectures.Proc.

Loss Functions for Predictor-based Neural Architecture Search Ta-gates: An encoding scheme for neu- ral network architectures.Proc

Reference 26

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Observation 19a41f4c-dc2e-4015-a85c-3f76ca72d3fe · outbound

This paper cites Efficient neural architecture search via parameters sharing.

Loss Functions for Predictor-based Neural Architecture Search Efficient neural architecture search via parameters sharing

Reference 27

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Observation e6f80be7-7b33-4048-a9a2-f8753fb253ec · outbound

This paper cites Nas-bench-graph: Benchmarking graph neu- ral architecture search.Proc.

Loss Functions for Predictor-based Neural Architecture Search Nas-bench-graph: Benchmarking graph neu- ral architecture search.Proc

Reference 28

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Source-reported events for the cited work

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Observation 2fb011bd-cb32-42cc-aa3b-4445d0360200 · outbound

This paper cites Large-scale evolution of image classifiers.

Loss Functions for Predictor-based Neural Architecture Search Large-scale evolution of image classifiers

Reference 29

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Observation 4b204b68-6718-4e4f-962e-17a5962dea71 · outbound

This paper cites Bridging the gap between sample-based and one-shot neural architecture search with bonas.Proc.

Loss Functions for Predictor-based Neural Architecture Search Bridging the gap between sample-based and one-shot neural architecture search with bonas.Proc

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Observation cf543668-21f3-484c-aa25-b7cca25f8654 · outbound

This paper cites The lambdaloss framework for ranking metric optimization.

Loss Functions for Predictor-based Neural Architecture Search The lambdaloss framework for ranking metric optimization

Reference 31

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Source-reported events for the cited work

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Observation 52b5aea8-08de-4ac1-8abe-c74de2e06517 · outbound

This paper cites Textnas: A neural architecture search space tailored for text representation.

Loss Functions for Predictor-based Neural Architecture Search Textnas: A neural architecture search space tailored for text representation

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 556609c1-c6a1-4b30-b2fd-33fa1ade8daf · outbound

This paper cites Npenas: Neural predictor guided evo- lution for neural architecture search.IEEE Transactions on Neural Networks and Learning Systems, 34(11):8441–8455,.

Loss Functions for Predictor-based Neural Architecture Search Npenas: Neural predictor guided evo- lution for neural architecture search.IEEE Transactions on Neural Networks and Learning Systems, 34(11):8441–8455,

Reference 33

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Source-reported events for the cited work

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Observation 05d817a7-8e56-40e0-874f-e0038b408dab · outbound

This paper cites Neural predictor for neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Neural predictor for neural architecture search

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 11d8dc3b-8664-4b6f-a969-0fb1d91517f2 · outbound

This paper cites Wsabie: Scaling up to large vocabulary image annotation.

Loss Functions for Predictor-based Neural Architecture Search Wsabie: Scaling up to large vocabulary image annotation

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:33.649375Z digest=sha256:d70cc116e8d22dadcea230b4ac177ac7a83196b45a9a372998335892ca93fea1

Observation 1fb00180-bea6-4daf-af0b-bc0ef310c247 · outbound

This paper cites Bananas: Bayesian optimization with neural architectures for neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Bananas: Bayesian optimization with neural architectures for neural architecture search

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:37.114999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:33.731583Z digest=sha256:5c6e4aff78de03a755e1a174e01070621509389285d9b0bf6ab4a1072d42cfca

Observation 9f3dd2aa-7448-4e50-8b74-eb0c1f932dba · outbound

This paper cites How powerful are performance predictors in neural architecture search?Proc.

Loss Functions for Predictor-based Neural Architecture Search How powerful are performance predictors in neural architecture search?Proc

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:36.798494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:33.791994Z digest=sha256:ed54773ae5c0a9c3b817f695ef653c7cdb9af9f3df0c2f0171d8dfb5ae8b1cea

Observation cf4022c9-ffe5-4036-a7d7-67521d0783ba · outbound

This paper cites Stronger nas with weaker predictors.

Loss Functions for Predictor-based Neural Architecture Search Stronger nas with weaker predictors

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:36.496827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:33.901096Z digest=sha256:ab20871b02402e92199c6a2b4b1da51f2b859c157797f403f9a287219f1e4a21

Observation a7849f54-6c39-4b7f-a993-a9b3f97c4a48 · outbound

This paper cites Listwise approach to learning to rank: theory and algorithm.

Loss Functions for Predictor-based Neural Architecture Search Listwise approach to learning to rank: theory and algorithm

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:36.204377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:33.975340Z digest=sha256:b2ca2f489b14c12aa26e3a61f2196848fdf52bfba3c24430e5e2f8d0281f6e83

Observation d2df80f7-86be-497e-9802-5432dfc07ed9 · outbound

This paper cites Renas: Relativistic evalu- ation of neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Renas: Relativistic evalu- ation of neural architecture search

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:35.904595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:34.083851Z digest=sha256:2390ed7d4239738a55d9857a926cd79038445bf9b0e712c0aaf39234824f2699

Observation 23416df1-63f5-4580-aa3b-3f82af918df1 · outbound

This paper cites Cate: Computation-aware neural architecture encoding with trans- formers.

Loss Functions for Predictor-based Neural Architecture Search Cate: Computation-aware neural architecture encoding with trans- formers

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:35.638899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:34.194422Z digest=sha256:fc6ea2006ec04b0e4850660320cf77bd3060ab633f8f937cd1a5e60db13d3188

Observation a04880bb-7bce-4fb3-82a4-330f0eec608f · outbound

This paper cites Nar-former: Neural architecture representation learning towards holistic attributes prediction.

Loss Functions for Predictor-based Neural Architecture Search Nar-former: Neural architecture representation learning towards holistic attributes prediction

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:35.414451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:34.295054Z digest=sha256:ec95eceeddd74de048fffaeb0cc0ab223cb1a9d5017881b8e7862718c14a7a3f

Observation ce08c5a3-6e9d-41cd-ada7-16d9133ab82a · outbound

This paper cites Nas-bench-101: Towards reproducible neural architecture search.

Loss Functions for Predictor-based Neural Architecture Search Nas-bench-101: Towards reproducible neural architecture search

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:35.230919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:34.410345Z digest=sha256:de74c46c7963c6ed0ff6b15373fefa16fd0c84975b8e81ed3e21a3f4cde1a44d

Observation 93c81ca0-bc4a-4851-a6ea-d417d0188c8f · outbound

This paper cites Dclp: Neu- ral architecture predictor with curriculum contrastive learn- ing.

Loss Functions for Predictor-based Neural Architecture Search Dclp: Neu- ral architecture predictor with curriculum contrastive learn- ing

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:35.022986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:34.510792Z digest=sha256:2af842d95d15d8396b11ef192a728d1f35f1cdf9f405d7a06ace54f2f56b7912

Observation f665fed3-f758-4e86-899b-0ddf37f2ed51 · outbound

This paper cites Neural architecture search with reinforcement learning.

Loss Functions for Predictor-based Neural Architecture Search Neural architecture search with reinforcement learning

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:20:34.822872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:20:34.584120Z digest=sha256:6ff6b5740c36e2c9f20fa7bd32bfff1349f076bf3defcc5b3ae26683f71cfe08

Pith citing papers

No inbound Pith citation observations are available.