CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor | Paper Citation Record

Observation b62a2204-18d5-456b-bf4e-29cf9e67dc9f · outbound

This paper cites Zero-Cost Proxies for Lightweight NAS.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Zero-Cost Proxies for Lightweight NAS

Reference 1

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Observation 1186c38b-1689-4eca-85f9-0cfc2fff62fb · outbound

This paper cites Random search for hyper-parameter optimization.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Random search for hyper-parameter optimization

Reference 2

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Observation c228f78d-00cd-4424-a462-059cb78d1980 · outbound

This paper cites Progres- sive differentiable architecture search: Bridging the depth gap between search and evaluation.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Progres- sive differentiable architecture search: Bridging the depth gap between search and evaluation

Reference 3

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Observation 26cbbe9e-27b6-4345-8c44-ac296bb2b789 · outbound

This paper cites Drnas: Dirichlet neu- ral architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Drnas: Dirichlet neu- ral architecture search

Reference 4

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Observation 83fe5f6f-b43c-42fb-a8fe-b7eb33774294 · outbound

This paper cites Not all operations contribute equally: Hier- archical operation-adaptive predictor for neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Not all operations contribute equally: Hier- archical operation-adaptive predictor for neural architecture search

Reference 5

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Observation bda9754f-ea97-44fa-9ce5-f3a4088b4e28 · outbound

This paper cites Fair darts: Eliminating unfair advantages in differentiable ar- chitecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Fair darts: Eliminating unfair advantages in differentiable ar- chitecture search

Reference 6

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Observation 7e0aa1c4-2ad0-4a9e-994d-269be28b3a21 · outbound

This paper cites Environment inference for invariant learning.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Environment inference for invariant learning

Reference 7

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Observation 81bc993d-ce29-4e28-ad3a-aaae71279d0b · outbound

This paper cites NAS-Bench-201: Extending the scope of reproducible neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor NAS-Bench-201: Extending the scope of reproducible neural architecture search

Reference 8

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Observation 224f1ce5-db54-4cfa-a9d9-61aff2287808 · outbound

This paper cites Searching for a robust neu- ral architecture in four gpu hours.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Searching for a robust neu- ral architecture in four gpu hours

Reference 9

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Observation 7052c531-197e-4163-93a2-7e721633c55e · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor TransNAS-Bench-101: Improving transferability and generalizability of cross-task neural architecture search

Reference 10

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Observation e78489e4-1df7-4ef0-b5e7-65f13bcc3898 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Brp-nas: Prediction-based nas using gcns

Reference 11

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Observation 6862d597-3bdf-4e89-8172-b4fcbacf38b5 · outbound

This paper cites Neural architecture search: A survey.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Neural architecture search: A survey

Reference 12

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Observation b66c0617-5b24-441e-919b-792f5653560b · outbound

This paper cites Generalizing few-shot NAS with gradient matching.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Generalizing few-shot NAS with gradient matching

Reference 13

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Observation aa67d02d-c3ec-4899-8c8a-d8c54645b6d9 · outbound

This paper cites Angle-based search space shrinking for neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Angle-based search space shrinking for neural architecture search

Reference 14

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Observation eb299312-7701-4f74-9947-ffadcde1b8d7 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Arch-Graph: Acyclic architecture relation predictor for task-transferable neural ar- chitecture search

Reference 15

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Observation 201ee0f2-749e-489f-ae36-9704c5d898fa · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Flowerformer: Empowering neural architecture encod- ing using a flow-aware graph transformer

Reference 16

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Observation 0fae98cd-dfc8-4407-af39-becbb5466729 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Graph masked au- toencoder enhanced predictor for neural architecture search

Reference 17

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Observation 4bfe9eb6-cb91-4e77-83b2-f3c6a2f1ed8b · outbound

This paper cites Neural architecture search with bayesian optimisation and optimal transport.Ad- vances in neural information processing systems , 31, 2018.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Neural architecture search with bayesian optimisation and optimal transport.Ad- vances in neural information processing systems , 31, 2018

Reference 18

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Observation 6b773a1b-c6ed-4bc9-9a97-8a604a88b27e · outbound

This paper cites Semi-supervised classi- fication with graph convolutional networks.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Semi-supervised classi- fication with graph convolutional networks

Reference 19

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Observation 090d67a0-81bc-4113-b4d7-fbeb150d9bd6 · outbound

This paper cites Nas-bench-nlp: neural architecture search benchmark for natural language processing.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Nas-bench-nlp: neural architecture search benchmark for natural language processing

Reference 20

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Observation bd72b23b-af93-4deb-ad3b-662228c7a8c3 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Learning multiple layers of features from tiny images

Reference 21

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Observation a20f152f-93ab-4476-a533-852b075cb609 · outbound

This paper cites Az-nas: Assembling zero- cost proxies for network architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Az-nas: Assembling zero- cost proxies for network architecture search

Reference 22

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Observation bb17f158-8380-4e85-8527-ddff9f18a05f · outbound

This paper cites Random search and repro- ducibility for neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Random search and repro- ducibility for neural architecture search

Reference 23

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Observation b1c648c2-9c1d-418d-b3fe-eefb2d0adfe7 · outbound

This paper cites Improving one-shot NAS by suppressing the posterior fading.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Improving one-shot NAS by suppressing the posterior fading

Reference 24

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Observation cc6779ed-d4ee-40f0-b496-0c2b3277edbf · outbound

This paper cites DARTS: Differentiable architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor DARTS: Differentiable architecture search

Reference 25

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Observation 4c465fa4-a925-4f1f-8d31-b1eb43d67fa0 · outbound

This paper cites Homogeneous ar- chitecture augmentation for neural predictor.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Homogeneous ar- chitecture augmentation for neural predictor

Reference 26

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Observation 21037da5-d988-4716-bcb7-bd0d319cf1b9 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Bridge the gap between architecture spaces via a cross-domain predictor

Reference 27

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Observation c6b9308c-f44b-489b-9639-a994392c7ad2 · outbound

This paper cites TNASP: A transformer-based NAS predictor with a self- evolution framework.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor TNASP: A transformer-based NAS predictor with a self- evolution framework

Reference 28

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Observation d5c85e52-587d-4898-b1d1-cc69b56fdc70 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Pinat: A permutation invari- ance augmented transformer for nas predictor

Reference 29

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Observation a575f151-6f59-4766-80f0-b450d8c97cef · outbound

This paper cites PA&DA: Jointly sam- pling path and data for consistent NAS.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor PA&DA: Jointly sam- pling path and data for consistent NAS

Reference 30

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This paper cites Neural architecture optimization.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Neural architecture optimization

Reference 31

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Observation 787f2e8a-1b2a-4842-87c1-3580e55db4e5 · outbound

This paper cites Neural architecture search without training.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Neural architecture search without training

Reference 32

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Observation 8cdc2211-5063-4224-9811-339bdd6d9b38 · outbound

This paper cites Build- ing optimal neural architectures using interpretable knowl- edge.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Build- ing optimal neural architectures using interpretable knowl- edge

Reference 33

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Observation 20fbaa90-625d-4742-9cff-4ab76e02ca86 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor A generic graph-based neural architecture encoding scheme for predictor-based NAS

Reference 34

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Observation 0bc9a170-1290-4905-808b-82a575a2d9c6 · outbound

This paper cites Evaluat- ing efficient performance estimators of neural architectures.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Evaluat- ing efficient performance estimators of neural architectures

Reference 35

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Ta-gates: An encoding scheme for neu- ral network architectures

Reference 36

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Observation b3cd015c-69c4-46ed-adbf-0ed39b85aca4 · outbound

This paper cites Causality.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Causality

Reference 37

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Observation 6cbb647d-7c75-4b12-9df4-0ba4633196b5 · outbound

This paper cites Causal inference in statistics: A primer.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Causal inference in statistics: A primer

Reference 38

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This paper cites Models, reasoning and inference.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Models, reasoning and inference

Reference 39

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Observation bd9df181-a574-4430-859e-363d63d82f2e · outbound

This paper cites PRE-NAS: Evolutionary neu- ral architecture search with predictor.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor PRE-NAS: Evolutionary neu- ral architecture search with predictor

Reference 40

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Observation 4b5961a4-1558-4cba-8bbd-d0c8a41fc4b4 · outbound

This paper cites Regularized evolution for image classifier architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Regularized evolution for image classifier architecture search

Reference 41

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This paper cites A comprehensive survey of neural architecture search: Challenges and solu- tions.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor A comprehensive survey of neural architecture search: Challenges and solu- tions

Reference 42

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Observation 37175a45-f0c0-4025-bd50-b4aa6192cedb · outbound

This paper cites Interpretable neural architecture search via bayesian optimisation with weisfeiler-lehman kernels.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Interpretable neural architecture search via bayesian optimisation with weisfeiler-lehman kernels

Reference 43

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Observation ee2a4bb5-5cd9-43b3-a9a4-97e24236f885 · outbound

This paper cites Estimates of the regression coefficient based on kendall’s tau.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Estimates of the regression coefficient based on kendall’s tau

Reference 44

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Observation ac24cfd5-d6ba-401c-adaf-4a7f4fc5ead5 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Bridging the gap between sample-based and one-shot neural architecture search with BONAS

Reference 45

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Observation 90cacdd2-3386-4d84-8142-1eb40eb2023c · outbound

This paper cites Mnas- net: Platform-aware neural architecture search for mobile.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Mnas- net: Platform-aware neural architecture search for mobile

Reference 46

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Observation e28975f9-0318-4a44-9203-ebf4967c85c8 · outbound

This paper cites Invariant feature learning for generalized long-tailed classification.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Invariant feature learning for generalized long-tailed classification

Reference 47

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Observation 0a39d667-ca76-49ed-b50d-d0fb216c5a4e · outbound

This paper cites Attention is all you need.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Attention is all you need

Reference 48

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Observation 041d4daa-3600-4178-be34-a04b3c470230 · outbound

This paper cites On redundancy and diversity in cell-based neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor On redundancy and diversity in cell-based neural architecture search

Reference 49

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Observation c707054e-cf99-4e3b-b7fe-d6c61aa9a713 · outbound

This paper cites Visual commonsense R-CNN.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Visual commonsense R-CNN

Reference 50

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Observation 0e6ce800-5b45-48d4-b893-88d51e3e578f · outbound

This paper cites NPENAS: Neural predictor guided evolution for neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor NPENAS: Neural predictor guided evolution for neural architecture search

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.854931Z

Source-reported events for the cited work

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This paper cites Neural predictor for neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Neural predictor for neural architecture search

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.845375Z

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This paper cites BA- NANAS: Bayesian optimization with neural architectures for neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor BA- NANAS: Bayesian optimization with neural architectures for neural architecture search

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.836348Z

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This paper cites Stronger NAS with weaker predic- tors.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Stronger NAS with weaker predic- tors

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.827275Z

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This paper cites Representing long- 10 range context for graph neural networks with global atten- tion.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Representing long- 10 range context for graph neural networks with global atten- tion

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.817367Z

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Observation 738c42c5-4523-44bd-8d11-b8365b2b51c0 · outbound

This paper cites Shapley-NAS: Discovering operation contribution for neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Shapley-NAS: Discovering operation contribution for neural architecture search

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.808570Z

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Observation 88aea546-442d-4921-b9bd-94badafa53bf · outbound

This paper cites Genetic cnn.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Genetic cnn

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.799574Z

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Observation 0b3dd115-8327-4945-851b-e859ed9e0ec7 · outbound

This paper cites How Powerful are Graph Neural Networks?.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor How Powerful are Graph Neural Networks?

Reference 58

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This paper cites PC-DARTS: Par- tial channel connections for memory-efficient architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor PC-DARTS: Par- tial channel connections for memory-efficient architecture search

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.789777Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 89a31e6d-2fc1-440a-8565-a0e478eb79e9 · outbound

This paper cites Renas: Relativistic eval- uation of neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Renas: Relativistic eval- uation of neural architecture search

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.780064Z

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Observation 28aa2230-8a11-42a7-b2bf-1f7ef6a757f5 · outbound

This paper cites Does unsupervised architecture representation learning help neural architecture search? Advances in Neural Information Processing Systems, 33:12486–12498, 2020.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Does unsupervised architecture representation learning help neural architecture search? Advances in Neural Information Processing Systems, 33:12486–12498, 2020

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.769936Z

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Observation 73c12754-d0da-4806-a8d0-2e24d988f70a · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor CATE: Computation-aware neural architecture encoding with trans- formers

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.759879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5dac3692-38b3-4f11-9b3c-190503479368 · outbound

This paper cites NAR-Former: Neural architecture representa- tion learning towards holistic attributes prediction.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor NAR-Former: Neural architecture representa- tion learning towards holistic attributes prediction

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.749770Z

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Observation 78b310c8-59e6-478f-a2d8-b04d9d439c98 · outbound

This paper cites NAS-Bench-101: To- wards reproducible neural architecture search.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor NAS-Bench-101: To- wards reproducible neural architecture search

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.740176Z

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Observation d76af151-e66e-47f3-a947-48051f546acb · outbound

This paper cites Do transformers really perform badly for graph representation? Advances in neural information processing systems , 34: 28877–28888, 2021.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Do transformers really perform badly for graph representation? Advances in neural information processing systems , 34: 28877–28888, 2021

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.730421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8633e4b2-7fd6-4c86-ba26-d710476394b3 · outbound

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

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Dclp: Neu- ral architecture predictor with curriculum contrastive learn- ing

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.720414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b3db12af-60c5-4f16-944b-0e9650dcbf4f · outbound

This paper cites Neural Architecture Search with Reinforcement Learning.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Neural Architecture Search with Reinforcement Learning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T10:54:58.645487Z

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Observation 7208c9e5-48d8-467b-8914-821f8418cd80 · outbound

This paper cites Learning transferable architectures for scalable image recognition.

CARL: Causality-guided Architecture Representation Learning for an Interpretable Performance Predictor Learning transferable architectures for scalable image recognition

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:54:58.710034Z

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