Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-29T19:51:03.507433Z
Paper Citation Record · LEDGER
Towards Continuous-time Causal Foundation Models
As of 9 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 1 inbound Pith citation observation for arXiv:2605.28880.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T18:03:53.670706Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-04T03:29:29.726628Z
Reference resolution
2 of 2 outbound references displayed
- verified exact1
- verified fuzzy0
- unresolved1
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ce8811f7-726d-4965-aa62-c01e48df7a0d · outbound
This paper cites Rubanova, Y ., Chen, R.
Towards Continuous-time Causal Foundation Models Rubanova, Y ., Chen, R
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-06-29T19:51:03.507433Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ccfe1543-7064-4b42-abfa-d868eb8e33d1 · outbound
This paper cites Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit.
Towards Continuous-time Causal Foundation Models Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T19:53:55.474798Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
Observation 505a8b67-4aa3-4dfc-b6d2-60ef9fc58654 · inbound
Temporal Causal Prior-Data Fitted Networks for Panel Data with Learned Reliability Signals cites this paper.
Temporal Causal Prior-Data Fitted Networks for Panel Data with Learned Reliability Signals Towards Continuous-time Causal Foundation Models
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T03:29:29.729639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.