Paper Citation Record · LEDGER

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs

As of 15 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2509.00772.

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

pith.paper-citation-record.v1
2509.00772 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:19:11.815903Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T08:32:32.410473Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T08:34:05.462671Z

Reference resolution

24 of 24 outbound references displayed

verified exact4
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8d9307d-4fbb-4ac0-a4dd-20bc686b3987 · outbound

This paper cites Adaptive Universal Generalized PageRank Graph Neural Network.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Adaptive Universal Generalized PageRank Graph Neural Network

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.015533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 979aad24-9dc2-408a-80af-742d5693c4bb · outbound

This paper cites Principal Neighbourhood Aggregation for Graph Nets.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Principal Neighbourhood Aggregation for Graph Nets

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.055306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7682c4c-e3f5-43aa-bf60-45175b241504 · outbound

This paper cites Polynormer: Polynomial-Expressive Graph Transformer in Linear Time.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Polynormer: Polynomial-Expressive Graph Transformer in Linear Time

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.132238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93a78ab5-d828-444a-b789-fa0170ae10cb · outbound

This paper cites Neural Message Passing for Quantum Chemistry.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Neural Message Passing for Quantum Chemistry

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.243000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10fa268e-6b14-4358-8dcf-5818aecc64f5 · outbound

This paper cites Inductive Representation Learning on Large Graphs.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Inductive Representation Learning on Large Graphs

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.359918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 551a4a4f-4d49-4daa-9af0-ee40c2305504 · outbound

This paper cites High-Order Pooling for Graph Neural Networks with Tensor Decomposition.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs High-Order Pooling for Graph Neural Networks with Tensor Decomposition

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:19:12.852121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3f28ce7f-07ea-4188-b8f9-fdd54f9e4c80 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Semi-Supervised Classification with Graph Convolutional Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.519166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c51567b6-f4e8-4370-ab6f-23ff40d48678 · outbound

This paper cites Finding Global Homophily in Graph Neural Networks When Meeting Heterophily.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.595554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a67d44d9-5b69-4398-b064-e97f8e332adf · outbound

This paper cites Gated Graph Sequence Neural Networks.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Gated Graph Sequence Neural Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.671729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f194c9d0-a74c-4e43-b880-709d3641f23a · outbound

This paper cites DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:19:12.642520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9098da82-baf3-4620-a6cb-5b85a121a1d8 · outbound

This paper cites Improving Graph Neural Networks with Simple Architecture Design.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Improving Graph Neural Networks with Simple Architecture Design

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.813138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79625630-3a2f-415b-b8a7-20437397d768 · outbound

This paper cites A critical look at the evaluation of GNNs under heterophily: Are we really making progress?.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.866489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f12add5-756f-4757-82f5-f0dcc288e398 · outbound

This paper cites Edge Directionality Improves Learning on Heterophilic Graphs.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Edge Directionality Improves Learning on Heterophilic Graphs

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:10.948749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0a6eb72-1b60-418f-8426-76b06140778d · outbound

This paper cites Gradient Gating for Deep Multi-Rate Learning on Graphs.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Gradient Gating for Deep Multi-Rate Learning on Graphs

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:19:12.452536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 34b9edf3-ca05-474d-8bfb-2dc8d22b0b25 · outbound

This paper cites an unresolved cited work.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:11.094614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a20ecd-9c25-40d5-ad92-f937928e71b9 · outbound

This paper cites Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:11.186234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f61ccd4f-6924-4e08-a25b-d1de4b7bc970 · outbound

This paper cites an unresolved cited work.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-05T13:19:13.083483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d08870ec-52b5-43dd-a85a-8b7172a1a216 · outbound

This paper cites Directed Graph Convolutional Network.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Directed Graph Convolutional Network

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T13:19:12.201011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8da13e73-501d-4ff7-9a88-41ba16fb6b15 · outbound

This paper cites Graph Attention Networks.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Graph Attention Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:11.411295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdebe5a9-343f-4b6c-a866-f98757f27a89 · outbound

This paper cites A Comprehensive Survey on Graph Neural Networks.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs A Comprehensive Survey on Graph Neural Networks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:11.499175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aeacd075-9df1-4be6-b786-d9546bba34c4 · outbound

This paper cites an unresolved cited work.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:11.592755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2c3f277-601c-4cec-9622-67a6eb413f85 · outbound

This paper cites MagNet: A Neural Network for Directed Graphs.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs MagNet: A Neural Network for Directed Graphs

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-05T13:19:12.015708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 76ac5007-9920-4d57-8231-f891eadbf68c · outbound

This paper cites Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:11.815903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e07ee51-5caf-41d3-85ba-3572be7e65fb · outbound

This paper cites Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T13:19:11.672426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 4e635ee6-a430-406d-8c59-bcdc5b574f11 · inbound

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification cites this paper.

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:34:05.464423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.