Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Can we Constrain Concept Bottleneck Models to Learn Semantically Meaningful Input Features?
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2402.00912.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:27:38.365930Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T14:27:38.821066Z
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 d93cbb2c-092a-4216-a759-f8578d03b0e7 · inbound
Enhancing Performance of Explainable AI Models with Constrained Concept Refinement cites this paper.
Enhancing Performance of Explainable AI Models with Constrained Concept Refinement Can we Constrain Concept Bottleneck Models to Learn Semantically Meaningful Input Features?
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T14:27:38.826169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.