Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2009.11848.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T00:33:49.298172Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T20:12:38.299479Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 40282564-b28f-4394-99a1-3545fadd11cc · inbound
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges cites this paper.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Reference 102
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.041004Z
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 3c1b399f-6259-4e54-ab8a-c104186c7f9a · inbound
Massive Activations in Large Language Models cites this paper.
Massive Activations in Large Language Models How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Reference 95
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T07:02:53.944970Z
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 814e2d97-23ef-4d59-8955-d1a7c985e1a3 · inbound
SLIDE: A machine-learning based method for forced dynamic response estimation of multibody systems cites this paper.
SLIDE: A machine-learning based method for forced dynamic response estimation of multibody systems How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T20:43:25.649278Z
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 12a86789-62b3-4553-8fad-adf99922c6b3 · inbound
How Far is Video Generation from World Model: A Physical Law Perspective cites this paper.
How Far is Video Generation from World Model: A Physical Law Perspective How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Reference 13
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T11:13:41.467785Z
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 a2e8d594-2d08-4242-b589-9fd0748c403e · inbound
Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks cites this paper.
Beyond Interpolation: Extrapolative Reasoning with Reinforcement Learning and Graph Neural Networks How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:33:49.298172Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1fc4e69-2abd-4db8-8131-c0d5979ecdea · inbound
Parameter-Efficient Conditioning for Material Generalization in Graph-Based Simulators cites this paper.
Parameter-Efficient Conditioning for Material Generalization in Graph-Based Simulators How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T23:40:31.170691Z
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 4f6f6ac3-983f-4c1d-8a5c-a1b9699766c4 · inbound
Out-of-Distribution generalization of quantile regression with heavy tailed inputs: an SVM approach cites this paper.
Out-of-Distribution generalization of quantile regression with heavy tailed inputs: an SVM approach How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Reference 68
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-28T20:12:38.300780Z
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.