Paper Citation Record · LEDGER

Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2409.15114.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.15114 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:23:29.722356Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T21:35:04.155643Z

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 5f551f93-484d-4586-aa71-229149bffe5b · inbound

Multimodal-to-Text Prompt Engineering in Large Language Models Using Feature Embeddings for GNSS Interference Characterization cites this paper.

Multimodal-to-Text Prompt Engineering in Large Language Models Using Feature Embeddings for GNSS Interference Characterization Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T21:23:29.722356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a8bc8c0-29c4-4b26-84c7-31054fda9f26 · inbound

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization cites this paper.

5G-DIL: Domain Incremental Learning with Similarity-Aware Sampling for Dynamic 5G Indoor Localization Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:45:26.159914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca750558-d22f-4efb-8ca6-3ecd7381a6fc · inbound

GenAI for Energy-Efficient and Interference-Aware Compressed Sensing of GNSS Signals on a Google Edge TPU cites this paper.

GenAI for Energy-Efficient and Interference-Aware Compressed Sensing of GNSS Signals on a Google Edge TPU Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-30T21:35:04.157277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0691f2e7-1b91-4e68-bd79-cb21760619b3 · inbound

Real-time Pre-Correlation GNSS Interference Classification with Lightweight Learned Algorithms cites this paper.

Real-time Pre-Correlation GNSS Interference Classification with Lightweight Learned Algorithms Evaluating ML Robustness in GNSS Interference Classification, Characterization & Localization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T08:25:46.955989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.