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Paper Citation Record · LEDGER

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs

As of 19 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2507.10183.

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

pith.paper-citation-record.v1
2507.10183 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:46:34.134755Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

34 of 34 outbound references displayed

  • verified exact5
  • verified fuzzy9
  • unresolved18
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f62c29b6-e3af-4589-ab1a-5ffd20c6f19d · outbound

This paper cites Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs

Reference 1

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local_arxiv, observed 2026-08-06T17:46:34.592925Z

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Observation 967d2d3f-67f9-4514-9fe7-723df11cc5da · outbound

This paper cites GC-LSTM: Graph Convolution Embedded LSTM for Dynamic Link Prediction.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs GC-LSTM: Graph Convolution Embedded LSTM for Dynamic Link Prediction

Reference 2

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Observation 631a632c-ebe0-458f-9d9e-0d7b2b77cb42 · outbound

This paper cites On the evolution of random graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs On the evolution of random graphs

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 17751001-5330-436f-91fc-146a7c545030 · outbound

This paper cites A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs A Comprehensive Survey of Dynamic Graph Neural Networks: Models, Frameworks, Benchmarks, Experiments and Challenges

Reference 4

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Observation ac90421a-006c-4a17-b0cf-be992535f0fc · outbound

This paper cites TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs

Reference 5

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Observation 56411e25-7def-41a3-8dc6-71c5ceff6f3b · outbound

This paper cites Long Range Propagation on Continuous-Time Dynamic Graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Long Range Propagation on Continuous-Time Dynamic Graphs

Reference 6

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Observation beba5196-815a-4595-9c45-c1b732b5eb9d · outbound

This paper cites Stochastic blockmodels: First steps.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Stochastic blockmodels: First steps

Reference 7

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Observation 66925694-9f49-4acf-8012-d694aec0be9f · outbound

This paper cites Tempo- ral graph benchmark for machine learning on temporal graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Tempo- ral graph benchmark for machine learning on temporal graphs

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 313f0491-69ce-4540-8e1a-58cd9c68684e · outbound

This paper cites Utg: Towards a unified view of snapshot and event based models for temporal graphs,.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Utg: Towards a unified view of snapshot and event based models for temporal graphs,

Reference 9

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 038fc9fe-54fa-4062-a1cb-6b66f1d95608 · outbound

This paper cites CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

Reference 10

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Observation 8cedcc70-2215-48e4-abe0-f1f591ceaa9a · outbound

This paper cites Representation learning for dynamic graphs: A survey.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Representation learning for dynamic graphs: A survey

Reference 11

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7aff6ef7-c4ae-433b-9a4f-0a6456f215c3 · outbound

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

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Semi-Supervised Classification with Graph Convolutional Networks

Reference 12

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Observation d0abb780-3bcd-48b7-9927-2a88b914e6b9 · outbound

This paper cites Predicting dynamic embedding trajectory in temporal interaction networks.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Predicting dynamic embedding trajectory in temporal interaction networks

Reference 13

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Observation 27217f72-1a4a-43bd-ab13-d63e7f5d96d7 · outbound

This paper cites Neighborhood-aware scalable temporal network representation learning.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Neighborhood-aware scalable temporal network representation learning

Reference 14

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation dad71798-aca3-4ab0-8784-9641e04dc177 · outbound

This paper cites Sandy" Pentland. Sensing the.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Sandy" Pentland. Sensing the

Reference 15

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Observation 185d5759-6035-4f49-b900-61b64e9109cb · outbound

This paper cites Behaviour Suite for Reinforcement Learning.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Behaviour Suite for Reinforcement Learning

Reference 16

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Observation 91152c73-5c4c-4611-ba6a-5f8be5d75b53 · outbound

This paper cites an unresolved cited work.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Unresolved cited work

Reference 17

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b1631e99-b51c-4652-b37d-56fdf36503db · outbound

This paper cites EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs

Reference 18

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Observation 237c6da9-423a-42f5-b2da-0e8287618a5a · outbound

This paper cites Towards Better Evaluation for Dynamic Link Prediction.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Towards Better Evaluation for Dynamic Link Prediction

Reference 19

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local_arxiv, observed 2026-08-06T17:46:34.458254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 13b66029-0628-4233-8d6c-1f28fe5ac70b · outbound

This paper cites Temporal Graph Networks for Deep Learning on Dynamic Graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Temporal Graph Networks for Deep Learning on Dynamic Graphs

Reference 20

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Observation 65af2853-c0e9-4d63-a25d-66a7b14e3bed · outbound

This paper cites Graphpulse: Topological representations for temporal graph property prediction.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Graphpulse: Topological representations for temporal graph property prediction

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation dae3bbcd-7940-4149-9698-ef4a8de79075 · outbound

This paper cites The enron email dataset database schema and brief statistical report.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs The enron email dataset database schema and brief statistical report

Reference 22

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 51216680-5507-4d77-9b02-1162049084a1 · outbound

This paper cites Static graph approximations of dynamic contact networks for epidemic forecasting.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Static graph approximations of dynamic contact networks for epidemic forecasting

Reference 23

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2409d7f6-f1ea-477f-8b87-1d4130d47b4e · outbound

This paper cites MiNT: Multi-Network Training for Transfer Learning on Temporal Graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs MiNT: Multi-Network Training for Transfer Learning on Temporal Graphs

Reference 24

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Observation 61b54d9f-d45f-42f1-909e-bfc835a66678 · outbound

This paper cites Foundations and modeling of dynamic networks using dynamic graph neural networks: A survey.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Foundations and modeling of dynamic networks using dynamic graph neural networks: A survey

Reference 25

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Observation 92813129-e67e-4e7b-93d7-f64b8e24d8a0 · outbound

This paper cites Provably expressive temporal graph networks.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Provably expressive temporal graph networks

Reference 26

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Observation eb7ae8f0-714c-4b7a-b0ee-7c948f60b15b · outbound

This paper cites Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification

Reference 27

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Observation 1bd44d10-e9ee-4e80-9265-0681446f3076 · outbound

This paper cites Graph Attention Networks.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Graph Attention Networks

Reference 28

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Observation a77b1a1d-123a-412f-a01a-4c2ef15a3e41 · outbound

This paper cites Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

Reference 29

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Observation 8da9ac64-c103-4a83-8862-f998b5cabaf4 · outbound

This paper cites Inductive representation learning on temporal graphs, 2020.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Inductive representation learning on temporal graphs, 2020

Reference 30

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raw_fallback, observed 2026-08-06T17:46:34.599372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 45e3107a-8676-4369-9b76-affca63deecf · outbound

This paper cites TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs TGB-Seq Benchmark: Challenging Temporal GNNs with Complex Sequential Dynamics

Reference 31

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local_arxiv, observed 2026-08-06T17:46:34.354641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 14f732f4-4ef6-472a-b8d8-c79d19e59399 · outbound

This paper cites Towards Better Dynamic Graph Learning: New Architecture and Unified Library.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs Towards Better Dynamic Graph Learning: New Architecture and Unified Library

Reference 32

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local_arxiv, observed 2026-08-06T17:46:34.344990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 97bc75f6-1aaa-4426-abef-25d1bfd160a2 · outbound

This paper cites T-gcn: A temporal graph convolutional network for traffic prediction.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs T-gcn: A temporal graph convolutional network for traffic prediction

Reference 33

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Observation 2b40ce55-c6fe-4fb5-9cf2-f1e299b7626d · outbound

This paper cites UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs.

T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs

Reference 2024

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local_arxiv, observed 2026-08-06T17:46:34.560673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Pith citing papers

No inbound Pith citation observations are available.