Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploring the Interplay of Interpretability and Robustness in Deep Neural Networks: A Saliency-guided Approach
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.06278.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T16:56:08.944828Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T16:56:16.745849Z
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 782b3e4d-0fe7-495d-a1a9-7e285baa4583 · inbound
Adversarial Examples Are Not Bugs, They Are Superposition cites this paper.
Adversarial Examples Are Not Bugs, They Are Superposition Exploring the Interplay of Interpretability and Robustness in Deep Neural Networks: A Saliency-guided Approach
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T16:56:16.824963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation d2e1a86a-324d-490d-8a93-dbc5f468991c · inbound
CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization cites this paper.
CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization Exploring the Interplay of Interpretability and Robustness in Deep Neural Networks: A Saliency-guided Approach
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T23:30:20.273385Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.