Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-14T04:33:36.094446Z
Paper Citation Record · LEDGER
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration
As of 14 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2608.08689.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
26 of 26 outbound references displayed
- verified exact1
- verified fuzzy15
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 5aeee118-90f1-49a4-a733-d258ef637649 · outbound
This paper cites World Models.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration World Models
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:35.653629Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8be5ca5a-49a2-478b-961e-840d57604078 · outbound
This paper cites Learning Latent Dynamics for Planning from Pixels.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Learning Latent Dynamics for Planning from Pixels
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:37.198690Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 87af7403-f33e-4d36-b0c4-f506f1e38f80 · outbound
This paper cites Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, and Koray Kavukcuoglu.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, and Koray Kavukcuoglu
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:37.185149Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 38772879-b796-494a-9db5-1866ec8fa964 · outbound
This paper cites Relational inductive biases, deep learning, and graph networks.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Relational inductive biases, deep learning, and graph networks
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:35.713902Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6168aa98-87c1-44f0-90b2-cd5a83edff62 · outbound
This paper cites Schoenholz, Patrick F.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Schoenholz, Patrick F
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:37.171279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation bb763e55-dbd4-4440-970e-9a4eee7a67cd · outbound
This paper cites Semi-Supervised Classification with Graph Convolutional Networks.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Semi-Supervised Classification with Graph Convolutional Networks
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:35.730502Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1cc2b391-ccdd-4ab4-893e-df69412c72a2 · outbound
This paper cites Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4470–4479, 2018.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Proceedings of the 35th International Conference on Machine Learning, PMLR 80:4470–4479, 2018
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:37.139868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4768d4c7-9afd-4b2d-954c-fdf86135ca79 · outbound
This paper cites Learning to Simulate Complex Physics with Graph Networks.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Learning to Simulate Complex Physics with Graph Networks
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:37.047059Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 39318514-8cb0-4d2e-b23f-346e7e54a648 · outbound
This paper cites Temporal Graph Networks for Deep Learning on Dynamic Graphs.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Temporal Graph Networks for Deep Learning on Dynamic Graphs
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:35.743362Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3228621e-4e0e-4c0d-88c9-de3f40e5888f · outbound
This paper cites Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.970924Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 08deb0cf-d012-4896-b7fb-e284dc50c752 · outbound
This paper cites Forrester.
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.957376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d2a37f48-c916-49de-b646-e157f8e2b0e2 · outbound
This paper cites Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.944011Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 92e35a56-d375-467f-919a-f6dc9b55f3a6 · outbound
This paper cites Graph World Model.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Graph World Model
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.929828Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 69508b2e-2560-4700-9dcf-08c2384a38ba · outbound
This paper cites Graph World Models: Concepts, Taxonomy, and Future Directions.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Graph World Models: Concepts, Taxonomy, and Future Directions
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:35.765025Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ea982aa-ae7a-4b53-8432-790ca92eed33 · outbound
This paper cites Understanding Rollout Error in Graph World Models.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Understanding Rollout Error in Graph World Models
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T04:33:36.237769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation cdd756c6-4dc7-4349-8faf-83b1c6589660 · outbound
This paper cites Learning Physical Constraints with Neural Projec- tions.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Learning Physical Constraints with Neural Projec- tions
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.866339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation e713e259-1486-4b26-aea1-6067ea618538 · outbound
This paper cites Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:35.931758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e301bcdd-22c5-4340-b0fa-6bb3bcba21c9 · outbound
This paper cites Long Short-Term Memory.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Long Short-Term Memory
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.798997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 7a6195e7-3f20-4984-9b20-e76b279979a6 · outbound
This paper cites T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:36.064899Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1cf6746f-4774-4b19-9a0f-7c8a92d3aa42 · outbound
This paper cites Physics-informed neural net- works: A deep learning framework for solving forward and inverse problems involving non- linear partial differential equations.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Physics-informed neural net- works: A deep learning framework for solving forward and inverse problems involving non- linear partial differential equations
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:36.068853Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 825272b5-11f1-4695-90fb-3cca2b8faa75 · outbound
This paper cites Lagrangian Neural Networks.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Lagrangian Neural Networks
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T04:33:36.073371Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e7bc986-9091-4294-a280-9c4041bd14dd · outbound
This paper cites GNNEx- plainer: Generating Explanations for Graph Neural Networks.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration GNNEx- plainer: Generating Explanations for Graph Neural Networks
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.700244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a845b15c-1b52-4b0e-9fd4-4c3f2f38166a · outbound
This paper cites Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.677598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 23d59821-e726-4598-805d-45e1bccb36ff · outbound
This paper cites Vrachimis, Demetrios G.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Vrachimis, Demetrios G
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.637302Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 31238549-7e35-4fb6-b749-663278703df6 · outbound
This paper cites an unresolved cited work.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Unresolved cited work
Reference 25
- Resolution
- unresolved
- raw_fallback, observed 2026-08-14T04:33:36.505345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a24f5df5-dd9c-4283-a316-feaea8eee9ee · outbound
This paper cites Birchfield, Ti Xu, Kathleen M.
A Structural Dynamics Graph World Model: Unified Modeling, Constrained Rollout, and Interpretable Calibration Birchfield, Ti Xu, Kathleen M
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-14T04:33:36.455012Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Pith citing papers
No inbound Pith citation observations are available.