Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep Submodular Functions
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1701.08939.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T12:58:51.370459Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-06-29T08:33:14.776581Z
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 2fa9bb20-b7fa-41e3-914b-7b79a3c742a4 · inbound
How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.
How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Deep Submodular Functions
Reference 88
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T08:33:14.777776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b324a447-cc89-4bc2-88aa-4777982c89fa · inbound
How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.
How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Deep Submodular Functions
Reference 88
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:58:51.370459Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 38418164-a74b-4c11-a42a-9b483a498582 · inbound
Advancing Optimal Subset Oracle via Learning Relaxation of Neural Set Functions cites this paper.
Advancing Optimal Subset Oracle via Learning Relaxation of Neural Set Functions Deep Submodular Functions
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T04:48:14.980753Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.