Chordless Structure: A Pathway to Simple and Expressive GNNs | Paper Citation Record

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This paper cites The Surprising Power of Graph Neural Networks with Random Node Initialization.

Chordless Structure: A Pathway to Simple and Expressive GNNs The Surprising Power of Graph Neural Networks with Random Node Initialization

Reference 1

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This paper cites Shortest path networks for graph property prediction.

Chordless Structure: A Pathway to Simple and Expressive GNNs Shortest path networks for graph property prediction

Reference 2

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This paper cites Breaking the limits of message passing graph neural networks.

Chordless Structure: A Pathway to Simple and Expressive GNNs Breaking the limits of message passing graph neural networks

Reference 3

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This paper cites Weisfeiler and lehman go cellular: Cw networks.Advances in neural information processing systems, 34:2625–2640, 2021.

Chordless Structure: A Pathway to Simple and Expressive GNNs Weisfeiler and lehman go cellular: Cw networks.Advances in neural information processing systems, 34:2625–2640, 2021

Reference 4

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This paper cites Bronstein.

Chordless Structure: A Pathway to Simple and Expressive GNNs Bronstein

Reference 5

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This paper cites Kagnns: Kolmogorov-arnold networks meet graph learning, 2024.

Chordless Structure: A Pathway to Simple and Expressive GNNs Kagnns: Kolmogorov-arnold networks meet graph learning, 2024

Reference 6

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Observation 45804ad7-eb36-490b-a490-11a2ff888d86 · outbound

This paper cites An end-to-end attention-based approach for learning on graphs, 2024.

Chordless Structure: A Pathway to Simple and Expressive GNNs An end-to-end attention-based approach for learning on graphs, 2024

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:14.151379Z

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Observation e4dbfa0b-7fcc-44ad-8e89-885c193a29a6 · outbound

This paper cites Can graph neural networks count substructures?Advances in neural information processing systems, 33:10383–10395, 2020.

Chordless Structure: A Pathway to Simple and Expressive GNNs Can graph neural networks count substructures?Advances in neural information processing systems, 33:10383–10395, 2020

Reference 8

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This paper cites Topology-informed graph transformer.arXiv preprint arXiv:2402.02005, 2024.

Chordless Structure: A Pathway to Simple and Expressive GNNs Topology-informed graph transformer.arXiv preprint arXiv:2402.02005, 2024

Reference 9

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Observation 1e34b3de-96f4-4aa1-9980-f7967154acf4 · outbound

This paper cites Cycle to clique (cy2c) graph neural network: A sight to see beyond neighborhood aggregation.

Chordless Structure: A Pathway to Simple and Expressive GNNs Cycle to clique (cy2c) graph neural network: A sight to see beyond neighborhood aggregation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:14.127774Z

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Observation b0a4e4ba-048f-4280-b711-459b470a0210 · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral filtering.Advances in neural information processing systems, 29, 2016.

Chordless Structure: A Pathway to Simple and Expressive GNNs Convolutional neural networks on graphs with fast localized spectral filtering.Advances in neural information processing systems, 29, 2016

Reference 11

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Observation fd730697-b82d-4390-89a2-9bd0a53e84b5 · outbound

This paper cites The expressive power of path based graph neural networks.

Chordless Structure: A Pathway to Simple and Expressive GNNs The expressive power of path based graph neural networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:14.105135Z

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Observation ee4a167f-8289-4e14-abd6-c5e949735a13 · outbound

This paper cites A Fair Comparison of Graph Neural Networks for Graph Classification.

Chordless Structure: A Pathway to Simple and Expressive GNNs A Fair Comparison of Graph Neural Networks for Graph Classification

Reference 13

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This paper cites How powerful are k-hop message passing graph neural networks.Advances in Neural Information Processing Systems, 35:4776–4790, 2022.

Chordless Structure: A Pathway to Simple and Expressive GNNs How powerful are k-hop message passing graph neural networks.Advances in Neural Information Processing Systems, 35:4776–4790, 2022

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:14.089163Z

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This paper cites Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning.Nature Methods, 17(2):184–192, 2020.

Chordless Structure: A Pathway to Simple and Expressive GNNs Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning.Nature Methods, 17(2):184–192, 2020

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:14.075378Z

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Observation a1264284-c671-464b-8c70-8ee2b9655bc3 · outbound

This paper cites Neural message passing for quantum chemistry.

Chordless Structure: A Pathway to Simple and Expressive GNNs Neural message passing for quantum chemistry

Reference 16

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This paper cites Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017.

Chordless Structure: A Pathway to Simple and Expressive GNNs Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017

Reference 17

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Observation 3346c757-831e-44fe-b889-9bb8bdbb2b8f · outbound

This paper cites Hamilton, Rex Ying, and Jure Leskovec.

Chordless Structure: A Pathway to Simple and Expressive GNNs Hamilton, Rex Ying, and Jure Leskovec

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:14.044000Z

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Observation 2e14b57f-b0c4-46cf-b484-8883cb830149 · outbound

This paper cites Toward a spectral theory of cellular sheaves.Journal of Applied and Computational Topology, 3(4):315–358, 2019.

Chordless Structure: A Pathway to Simple and Expressive GNNs Toward a spectral theory of cellular sheaves.Journal of Applied and Computational Topology, 3(4):315–358, 2019

Reference 19

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This paper cites Zinc: a free tool to discover chemistry for biology.Journal of chemical information and modeling, 52(7):1757–1768, 2012.

Chordless Structure: A Pathway to Simple and Expressive GNNs Zinc: a free tool to discover chemistry for biology.Journal of chemical information and modeling, 52(7):1757–1768, 2012

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:23:13.182718Z

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This paper cites PhD thesis, Dissertation, RWTH Aachen University, 2020, 2020.

Chordless Structure: A Pathway to Simple and Expressive GNNs PhD thesis, Dissertation, RWTH Aachen University, 2020, 2020

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:14.011848Z

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This paper cites Kipf and Max Welling.

Chordless Structure: A Pathway to Simple and Expressive GNNs Kipf and Max Welling

Reference 22

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This paper cites Geodesic graph neural network for efficient graph representation learning.Advances in neural information processing systems, 35:5896– 5909, 2022.

Chordless Structure: A Pathway to Simple and Expressive GNNs Geodesic graph neural network for efficient graph representation learning.Advances in neural information processing systems, 35:5896– 5909, 2022

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.991138Z

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This paper cites The expressive power of graph neural networks.Graph Neural Networks: Foundations, Frontiers, and Applications, pages 63–98, 2022.

Chordless Structure: A Pathway to Simple and Expressive GNNs The expressive power of graph neural networks.Graph Neural Networks: Foundations, Frontiers, and Applications, pages 63–98, 2022

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.976707Z

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Observation e45de988-5cf3-4f00-a09c-3cec1d97ba6f · outbound

This paper cites Sign and Basis Invariant Networks for Spectral Graph Representation Learning.

Chordless Structure: A Pathway to Simple and Expressive GNNs Sign and Basis Invariant Networks for Spectral Graph Representation Learning

Reference 25

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This paper cites Geniepath: Graph neural networks with adaptive receptive paths.

Chordless Structure: A Pathway to Simple and Expressive GNNs Geniepath: Graph neural networks with adaptive receptive paths

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.960940Z

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Observation 8f706744-902a-421c-bf08-ea707483ef26 · outbound

This paper cites Graph inductive biases in transformers without message passing.

Chordless Structure: A Pathway to Simple and Expressive GNNs Graph inductive biases in transformers without message passing

Reference 27

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This paper cites When subgraph isomorphism is really hard, and why this matters for graph databases.Journal of Artificial Intelligence Research, 61:723–759, 2018.

Chordless Structure: A Pathway to Simple and Expressive GNNs When subgraph isomorphism is really hard, and why this matters for graph databases.Journal of Artificial Intelligence Research, 61:723–759, 2018

Reference 28

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This paper cites Clustering of large databases of compounds: using the mdl “keys” as structural descriptors.Journal of chemical information and computer sciences, 37(3):443–448, 1997.

Chordless Structure: A Pathway to Simple and Expressive GNNs Clustering of large databases of compounds: using the mdl “keys” as structural descriptors.Journal of chemical information and computer sciences, 37(3):443–448, 1997

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.922527Z

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Observation c49d2c0e-fc93-483d-ac20-9e69276f3a9c · outbound

This paper cites Path neural networks: Expressive and accurate graph neural networks.

Chordless Structure: A Pathway to Simple and Expressive GNNs Path neural networks: Expressive and accurate graph neural networks

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.906636Z

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This paper cites TUDataset: A collection of benchmark datasets for learning with graphs.

Chordless Structure: A Pathway to Simple and Expressive GNNs TUDataset: A collection of benchmark datasets for learning with graphs

Reference 31

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This paper cites Weisfeiler and leman go sparse: Towards scalable higher-order graph embeddings.Advances in Neural Information Processing Systems, 33:21824–21840, 2020.

Chordless Structure: A Pathway to Simple and Expressive GNNs Weisfeiler and leman go sparse: Towards scalable higher-order graph embeddings.Advances in Neural Information Processing Systems, 33:21824–21840, 2020

Reference 32

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This paper cites Weisfeiler and leman go neural: Higher-order graph neural networks.

Chordless Structure: A Pathway to Simple and Expressive GNNs Weisfeiler and leman go neural: Higher-order graph neural networks

Reference 33

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This paper cites K-hop graph neural networks.

Chordless Structure: A Pathway to Simple and Expressive GNNs K-hop graph neural networks

Reference 34

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Observation fb331fd9-7bbf-4e51-a5a8-0e1c861e70b3 · outbound

This paper cites Deepinf: Social influence prediction with deep learning.

Chordless Structure: A Pathway to Simple and Expressive GNNs Deepinf: Social influence prediction with deep learning

Reference 35

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This paper cites Recipe for a general, powerful, scalable graph transformer.Advances in Neural Information Processing Systems, 35:14501–14515, 2022.

Chordless Structure: A Pathway to Simple and Expressive GNNs Recipe for a general, powerful, scalable graph transformer.Advances in Neural Information Processing Systems, 35:14501–14515, 2022

Reference 36

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This paper cites Effective consideration of ring structures in cast/cnmr for highly accurate 13c nmr chemical shift prediction.Tetrahedron, 61(31):7431–7437, 2005.

Chordless Structure: A Pathway to Simple and Expressive GNNs Effective consideration of ring structures in cast/cnmr for highly accurate 13c nmr chemical shift prediction.Tetrahedron, 61(31):7431–7437, 2005

Reference 37

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Chordless Structure: A Pathway to Simple and Expressive GNNs Unresolved cited work

Reference 38

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Observation df292ab6-b4a2-4447-9002-4fcf49a5e216 · outbound

This paper cites Dynamic edge-conditioned filters in convolutional neural networks on graphs.

Chordless Structure: A Pathway to Simple and Expressive GNNs Dynamic edge-conditioned filters in convolutional neural networks on graphs

Reference 39

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This paper cites Beyond homophily: Structure-aware path aggregation graph neural network.

Chordless Structure: A Pathway to Simple and Expressive GNNs Beyond homophily: Structure-aware path aggregation graph neural network

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.802369Z

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Observation 7623b795-c4ec-4b77-a9f8-a98edeb8987d · outbound

This paper cites Weisfeiler and lehman go paths: Learning topological features via path complexes.

Chordless Structure: A Pathway to Simple and Expressive GNNs Weisfeiler and lehman go paths: Learning topological features via path complexes

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.787664Z

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Observation 6bdfe8ac-1206-48f8-b530-a5ed397e5994 · outbound

This paper cites An efficient algorithm for enumerating chordless cycles and chordless paths.

Chordless Structure: A Pathway to Simple and Expressive GNNs An efficient algorithm for enumerating chordless cycles and chordless paths

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.773174Z

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This paper cites Graph Attention Networks.

Chordless Structure: A Pathway to Simple and Expressive GNNs Graph Attention Networks

Reference 43

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This paper cites The reduction of a graph to canonical form and the algebra which appears therein.nti, Series, 2(9):12–16, 1968.

Chordless Structure: A Pathway to Simple and Expressive GNNs The reduction of a graph to canonical form and the algebra which appears therein.nti, Series, 2(9):12–16, 1968

Reference 44

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This paper cites Self-supervised graph learning for recommendation.

Chordless Structure: A Pathway to Simple and Expressive GNNs Self-supervised graph learning for recommendation

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.750221Z

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This paper cites A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks.

Chordless Structure: A Pathway to Simple and Expressive GNNs A Non-Asymptotic Analysis of Oversmoothing in Graph Neural Networks

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Observation 159fbc63-6b39-4d84-a88e-aade13cd18d4 · outbound

This paper cites Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks.Decision Support Systems, 38(3):473–487, 2004.

Chordless Structure: A Pathway to Simple and Expressive GNNs Fighting organized crimes: using shortest-path algorithms to identify associations in criminal networks.Decision Support Systems, 38(3):473–487, 2004

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.735499Z

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This paper cites How Powerful are Graph Neural Networks?.

Chordless Structure: A Pathway to Simple and Expressive GNNs How Powerful are Graph Neural Networks?

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This paper cites Cycle representation learning for inductive relation prediction.

Chordless Structure: A Pathway to Simple and Expressive GNNs Cycle representation learning for inductive relation prediction

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.721053Z

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This paper cites Cycle invariant positional encoding for graph representation learning.

Chordless Structure: A Pathway to Simple and Expressive GNNs Cycle invariant positional encoding for graph representation learning

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.705580Z

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Observation 4f52391e-02fb-4dc0-b3d7-074c429eaaa3 · outbound

This paper cites Analyzing learned molec- ular representations for property prediction.Journal of chemical information and modeling, 59(8):3370–3388, 2019.

Chordless Structure: A Pathway to Simple and Expressive GNNs Analyzing learned molec- ular representations for property prediction.Journal of chemical information and modeling, 59(8):3370–3388, 2019

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.690787Z

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

Chordless Structure: A Pathway to Simple and Expressive GNNs Do transformers really perform badly for graph representation?Advances in neural information processing systems, 34:28877–28888, 2021

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.676052Z

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

Observation 0eb53fdb-01e2-4e71-b866-4f92a25ba56a · outbound

This paper cites Graph convolutional neural networks for web-scale recommender systems.

Chordless Structure: A Pathway to Simple and Expressive GNNs Graph convolutional neural networks for web-scale recommender systems

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T14:23:13.321725Z

Source-reported events for the cited work

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Observation 6b605208-4800-4ba8-a1fe-6196c658fffd · outbound

This paper cites Hierarchical graph representation learning with differentiable pooling.Advances in neural information processing systems, 31, 2018.

Chordless Structure: A Pathway to Simple and Expressive GNNs Hierarchical graph representation learning with differentiable pooling.Advances in neural information processing systems, 31, 2018

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T14:23:13.326482Z

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Observation 44c577d2-db20-4cf6-92fb-cc1f2c87ddb2 · outbound

This paper cites The Expressive Power of Graph Neural Networks: A Survey.

Chordless Structure: A Pathway to Simple and Expressive GNNs The Expressive Power of Graph Neural Networks: A Survey

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T14:23:13.331522Z

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Observation 584809c4-e37b-4e77-aba8-1bc44cba14e6 · outbound

This paper cites A complete expressiveness hierarchy for subgraph gnns via subgraph weisfeiler-lehman tests.

Chordless Structure: A Pathway to Simple and Expressive GNNs A complete expressiveness hierarchy for subgraph gnns via subgraph weisfeiler-lehman tests

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.645000Z

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

Observation cd8dc144-28f8-464b-8731-8a94cef9623d · outbound

This paper cites An end-to-end deep learning architecture for graph classification.

Chordless Structure: A Pathway to Simple and Expressive GNNs An end-to-end deep learning architecture for graph classification

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.630937Z

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.

Observation 5ee98142-c82b-4bc7-b15a-6836186e47c0 · outbound

This paper cites Nested graph neural networks.Advances in Neural Information Processing Systems, 34:15734–15747, 2021.

Chordless Structure: A Pathway to Simple and Expressive GNNs Nested graph neural networks.Advances in Neural Information Processing Systems, 34:15734–15747, 2021

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T14:23:13.344532Z

Source-reported events for the cited work

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Observation 8174e816-8212-499c-ba00-141114f1164c · outbound

This paper cites Limitations.

Chordless Structure: A Pathway to Simple and Expressive GNNs Limitations

Reference 59

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T14:23:13.608120Z

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.

Observation 5881e690-e63e-4ec6-b1ec-9d61e8a7325f · outbound

This paper cites Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects.

Chordless Structure: A Pathway to Simple and Expressive GNNs Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:23:13.594091Z

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