Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T14:18:39.145369Z
Paper Citation Record · LEDGER
AutoGrable: What Is a Good Graph for a Table?
As of 20 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2608.11431.
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 2026-08-20T06:33:59.587034+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
50 of 50 outbound references displayed
- verified exact2
- verified fuzzy29
- unresolved17
- parse uncertain0
- malformed identifier1
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 0496965f-6f90-4ef7-bf99-74814be0d657 · outbound
This paper cites Learning discrete structures for graph neural networks.
AutoGrable: What Is a Good Graph for a Table? Learning discrete structures for graph neural networks
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.718413Z
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 5977d640-9adb-41b9-a11c-ee9a351598ba · outbound
This paper cites Differentiable graph module (dgm) for graph convolutional networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(2):1606–1617, 2022.
AutoGrable: What Is a Good Graph for a Table? Differentiable graph module (dgm) for graph convolutional networks.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(2):1606–1617, 2022
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.633616Z
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 bd571dad-c036-4eca-bfe4-951339f3f138 · outbound
This paper cites OpenGSL: A comprehensive benchmark for graph structure learning.
AutoGrable: What Is a Good Graph for a Table? OpenGSL: A comprehensive benchmark for graph structure learning
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.537930Z
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 f2c4e405-2e0c-4678-8119-fe772e79e50e · outbound
This paper cites Position: Relational deep learning - graph representation learning on relational databases.
AutoGrable: What Is a Good Graph for a Table? Position: Relational deep learning - graph representation learning on relational databases
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.446726Z
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 c8057ee1-9047-42fe-b41c-a668e56b5b18 · outbound
This paper cites Autog: Towards automatic graph construction from tabular data.
AutoGrable: What Is a Good Graph for a Table? Autog: Towards automatic graph construction from tabular data
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.381570Z
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 8a3d6c85-efde-4bfc-bba4-71f7d6b4c801 · outbound
This paper cites From Features to Structure: Task-Aware Graph Construction for Relational and Tabular Learning with GNNs.
AutoGrable: What Is a Good Graph for a Table? From Features to Structure: Task-Aware Graph Construction for Relational and Tabular Learning with GNNs
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:37.828604Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d8189b64-b038-499d-91bc-45dc6ddb1e17 · outbound
This paper cites How powerful are graph neural networks? InInternational Conference on Learning Representations, 2019.
AutoGrable: What Is a Good Graph for a Table? How powerful are graph neural networks? InInternational Conference on Learning Representations, 2019
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.296376Z
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 88525067-62d1-4d47-8b56-5f43940313c9 · outbound
This paper cites Hamilton, Jan Eric Lenssen, Gaurav Rattan, and Martin Grohe.
AutoGrable: What Is a Good Graph for a Table? Hamilton, Jan Eric Lenssen, Gaurav Rattan, and Martin Grohe
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:37.942116Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a6ec3d6-20d4-4967-bf6a-4082ccaf5890 · outbound
This paper cites Grables: Tabular learning beyond independent rows.
AutoGrable: What Is a Good Graph for a Table? Grables: Tabular learning beyond independent rows
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:37.971885Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bcc5f16c-6188-4d3b-ab87-ae0a835a04d9 · outbound
This paper cites an unresolved cited work.
AutoGrable: What Is a Good Graph for a Table? Unresolved cited work
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:37.986039Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 688c443c-471b-4c50-ab29-82dee6dbf691 · outbound
This paper cites RDB2g-bench: A comprehensive benchmark for au- tomatic graph modeling of relational databases.
AutoGrable: What Is a Good Graph for a Table? RDB2g-bench: A comprehensive benchmark for au- tomatic graph modeling of relational databases
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.227619Z
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 ccbc2146-6636-473c-8385-2456a83258c8 · outbound
This paper cites Relbench: A benchmark for deep learning on relational databases.Advances in Neural Information Processing Systems, 37: 21330–21341, 2024.
AutoGrable: What Is a Good Graph for a Table? Relbench: A benchmark for deep learning on relational databases.Advances in Neural Information Processing Systems, 37: 21330–21341, 2024
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.164874Z
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 da4a883a-149d-4da3-8bac-5a2a75e7e6c0 · outbound
This paper cites RelBench v2: A Large-Scale Benchmark and Repository for Relational Data.
AutoGrable: What Is a Good Graph for a Table? RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:37.999098Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b2cf3f0f-cc45-4324-b672-5e0746cd744f · outbound
This paper cites Fraud Dataset Benchmark and Applications.
AutoGrable: What Is a Good Graph for a Table? Fraud Dataset Benchmark and Applications
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:38.004099Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 725c4239-a12a-40f7-a5e1-f03e80e22840 · outbound
This paper cites Tabarena: A living benchmark for machine learning on tabular data.
AutoGrable: What Is a Good Graph for a Table? Tabarena: A living benchmark for machine learning on tabular data
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:42.094454Z
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 da25bfa0-2a74-4660-9354-3d6eb36531ca · outbound
This paper cites word2vec, node2vec, graph2vec, x2vec: Towards a theory of vector embeddings of structured data.
AutoGrable: What Is a Good Graph for a Table? word2vec, node2vec, graph2vec, x2vec: Towards a theory of vector embeddings of structured data
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:38.094359Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f1757cba-61a2-4315-a710-52a4e7e8b56a · outbound
This paper cites WL meet VC.
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.978374Z
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 b48d11c9-f0b4-46f7-b71a-17c296c10b4c · outbound
This paper cites Towards bridging generalization and expressivity of graph neural networks.
AutoGrable: What Is a Good Graph for a Table? Towards bridging generalization and expressivity of graph neural networks
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.828507Z
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 ddafe076-de1b-448a-b28f-24a2009e090e · outbound
This paper cites Lutzeyer.
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.724147Z
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 22037b66-cb8d-48da-bfb6-2f9ce25b5fd4 · outbound
This paper cites Slaps: Self-supervision improves structure learning for graph neural networks.
AutoGrable: What Is a Good Graph for a Table? Slaps: Self-supervision improves structure learning for graph neural networks
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.660149Z
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 71efc502-2516-4dbf-9c4c-95f3798ebe34 · outbound
This paper cites Understanding over-squashing and bottlenecks on graphs via curvature.
AutoGrable: What Is a Good Graph for a Table? Understanding over-squashing and bottlenecks on graphs via curvature
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:38.292603Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fdc3b6c1-93cb-4ad8-9477-518400b9ba55 · outbound
This paper cites FoSR: First-order spectral rewiring for addressing oversquashing in GNNs.
AutoGrable: What Is a Good Graph for a Table? FoSR: First-order spectral rewiring for addressing oversquashing in GNNs
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:38.297537Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee0aff35-0097-4da0-b9db-5aa3e64deb26 · outbound
This paper cites Understanding oversquash- ing in GNNs through the lens of effective resistance.
AutoGrable: What Is a Good Graph for a Table? Understanding oversquash- ing in GNNs through the lens of effective resistance
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.555607Z
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 3c67d433-844d-4597-bb79-7e8e9e218b07 · outbound
This paper cites Graph neural networks for tabular data learning: A survey with taxonomy and directions.
AutoGrable: What Is a Good Graph for a Table? Graph neural networks for tabular data learning: A survey with taxonomy and directions
Reference 24
- Resolution
- verified exact
- doi, observed 2026-08-15T14:18:39.297789Z
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 518f69b6-3518-4e82-8500-46a16afc563d · outbound
This paper cites RelGNN: Composite message passing for relational deep learning.
AutoGrable: What Is a Good Graph for a Table? RelGNN: Composite message passing for relational deep learning
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.405322Z
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 0a119760-057c-4fe4-bd4b-9397eb349ce5 · outbound
This paper cites Kanatsoulis, Rishi Puri, Matthias Fey, and Jure Leskovec.
AutoGrable: What Is a Good Graph for a Table? Kanatsoulis, Rishi Puri, Matthias Fey, and Jure Leskovec
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.388781Z
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 780a901e-f4b6-437e-be79-26c827c82edf · outbound
This paper cites 4dbinfer: A 4d benchmarking toolbox for graph-centric predictive modeling on rdbs.
AutoGrable: What Is a Good Graph for a Table? 4dbinfer: A 4d benchmarking toolbox for graph-centric predictive modeling on rdbs
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:38.555103Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11375eba-aa2b-4e8c-ac0d-07a827507d22 · outbound
This paper cites Relatron: Automating relational machine learning over relational databases.
AutoGrable: What Is a Good Graph for a Table? Relatron: Automating relational machine learning over relational databases
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.320428Z
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 00392bd6-dad8-4b2c-a35b-f5a0a1e02d93 · outbound
This paper cites Kostylev, Mikael Monet, Jorge Pérez, Juan Reutter, and Juan Pablo Silva.
AutoGrable: What Is a Good Graph for a Table? Kostylev, Mikael Monet, Jorge Pérez, Juan Reutter, and Juan Pablo Silva
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.274190Z
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 f9d9c437-88a3-429d-8229-9da4e2822440 · outbound
This paper cites On the Rademacher Complexity of Graph Neural Networks: Unifying Expressivity and Geometry.
AutoGrable: What Is a Good Graph for a Table? On the Rademacher Complexity of Graph Neural Networks: Unifying Expressivity and Geometry
Reference 30
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-15T14:18:39.842877Z
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 f6ad560e-0222-48fd-b425-0a12b84c886b · outbound
This paper cites Weisfeiler-leman at the margin: When more expressivity matters.
AutoGrable: What Is a Good Graph for a Table? Weisfeiler-leman at the margin: When more expressivity matters
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.242985Z
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 be6a351f-6077-4b26-a082-410a10180c06 · outbound
This paper cites Iterative deep graph learning for graph neural networks: Better and robust node embeddings.
AutoGrable: What Is a Good Graph for a Table? Iterative deep graph learning for graph neural networks: Better and robust node embeddings
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.175448Z
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 d441d635-6e2b-4411-9f34-c66d4ec8a348 · outbound
This paper cites A Survey on Graph Structure Learning: Progress and Opportunities.
AutoGrable: What Is a Good Graph for a Table? A Survey on Graph Structure Learning: Progress and Opportunities
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T14:18:38.794658Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c2310406-8359-4f69-a359-b50787b0fafb · outbound
This paper cites On the bottleneck of graph neural networks and its practical implications.
AutoGrable: What Is a Good Graph for a Table? On the bottleneck of graph neural networks and its practical implications
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:41.019414Z
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 bb9fdcaa-b336-4a07-851f-375d4d369d53 · outbound
This paper cites Accurate predictions on small data with a tabular foundation model.Nature, 637(8045):319–326, 2025.
AutoGrable: What Is a Good Graph for a Table? Accurate predictions on small data with a tabular foundation model.Nature, 637(8045):319–326, 2025
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.938374Z
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 4d983a95-6225-406b-90e4-f16b16b61390 · outbound
This paper cites TabICL: A tabular foundation model for in-context learning on large data.
AutoGrable: What Is a Good Graph for a Table? TabICL: A tabular foundation model for in-context learning on large data
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.911888Z
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 95b9b5f4-95d0-43e9-8ab7-3639e36a14f1 · outbound
This paper cites Graphland: Evaluating graph machine learning models on diverse industrial data.
AutoGrable: What Is a Good Graph for a Table? Graphland: Evaluating graph machine learning models on diverse industrial data
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.752351Z
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 7556959f-0ace-4b38-a1e7-97101d7a0969 · outbound
This paper cites Database views as explanations for relational deep learning.arXiv preprint arXiv:2509.09482, 2025.
AutoGrable: What Is a Good Graph for a Table? Database views as explanations for relational deep learning.arXiv preprint arXiv:2509.09482, 2025
Reference 38
- Resolution
- verified exact
- raw_fallback, observed 2026-08-15T14:18:39.700358Z
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 fbd3d5a9-8559-4591-bdeb-d9b034f1245c · outbound
This paper cites Np-completeness of searches for smallest possible feature sets.
AutoGrable: What Is a Good Graph for a Table? Np-completeness of searches for smallest possible feature sets
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.655908Z
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 775dc015-aa95-4ea0-86ff-5f1733f09c73 · outbound
This paper cites Garey and David S.
AutoGrable: What Is a Good Graph for a Table? Garey and David S
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.590684Z
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 279f09de-b910-424c-94f1-9fc7dc85bd96 · outbound
This paper cites The presupposition throughout is geometric: an edge means proximity in some feature space.
AutoGrable: What Is a Good Graph for a Table? The presupposition throughout is geometric: an edge means proximity in some feature space
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.529505Z
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 d216d006-230a-44cd-bb1b-03edc608dfcf · outbound
This paper cites an unresolved cited work.
AutoGrable: What Is a Good Graph for a Table? Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:40.438257Z
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 57a9e845-ac8b-44a3-a19b-a91abac735a7 · outbound
This paper cites The downstream GNN also receives the unexpanded row features, so it can separate rows within a cell;J scores what the construction contributes, not the full model.
AutoGrable: What Is a Good Graph for a Table? The downstream GNN also receives the unexpanded row features, so it can separate rows within a cell;J scores what the construction contributes, not the full model
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.404200Z
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 7d4a68e3-809d-483c-850d-92b5ac0e45ce · outbound
This paper cites an unresolved cited work.
AutoGrable: What Is a Good Graph for a Table? Unresolved cited work
Reference 45
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:40.349974Z
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 3cbbbda7-eef5-4461-b890-c67bfa02c06b · outbound
This paper cites an unresolved cited work.
AutoGrable: What Is a Good Graph for a Table? Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:40.333502Z
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 2d494443-b247-451f-9593-5e3a8bad0fc0 · outbound
This paper cites an unresolved cited work.
AutoGrable: What Is a Good Graph for a Table? Unresolved cited work
Reference 47
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:40.252471Z
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 fe2d661b-9a2d-4bca-900a-318e103245cc · outbound
This paper cites Thus, adding columns creates a more expressive predictor, but also produces finer and potentially less well-supported cells.
AutoGrable: What Is a Good Graph for a Table? Thus, adding columns creates a more expressive predictor, but also produces finer and potentially less well-supported cells
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T14:18:40.230345Z
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 33532cce-45fc-40a6-bf95-9975f0692f09 · outbound
This paper cites an unresolved cited work.
AutoGrable: What Is a Good Graph for a Table? Unresolved cited work
Reference 49
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:40.081291Z
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 0f309da0-3760-4e75-9a96-43a81555a43a · outbound
This paper cites Simulated Credit Card Transactions generated using Sparkov.
AutoGrable: What Is a Good Graph for a Table? Simulated Credit Card Transactions generated using Sparkov
Reference 50
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-15T14:18:39.529168Z
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 786e4d81-ca4d-46ac-8d52-4bcb6967f007 · outbound
This paper cites an unresolved cited work.
AutoGrable: What Is a Good Graph for a Table? Unresolved cited work
Reference 2020
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T14:18:41.071388Z
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.
Pith citing papers
No inbound Pith citation observations are available.