Paper Citation Record · LEDGER

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices

As of 14 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2507.11053.

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

pith.paper-citation-record.v1
2507.11053 v1

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:25:34.079632Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

7 of 7 outbound references displayed

verified exact1
verified fuzzy4
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dc7b6c5e-1c0a-4489-8496-b40f5344703d · outbound

This paper cites an unresolved cited work.

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:25:35.017365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2c030dc1-3ab8-4480-a6c6-831079cee2a1 · outbound

This paper cites The Active Badge Location System.

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices The Active Badge Location System

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:35.150104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e274c65e-fd3a-485b-b531-2f397453296b · outbound

This paper cites AI and Machine Learning Driven Indoor Localization and Navigation with Mobile Embedded Systems.

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices AI and Machine Learning Driven Indoor Localization and Navigation with Mobile Embedded Systems

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-06T17:25:34.428532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b84afd21-9bae-47c4-83e7-dc5ef0a6bab0 · outbound

This paper cites Indoor Location Market by Component, Technology, Application, Vertical and Region - Global Forecast to 2028.

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices Indoor Location Market by Component, Technology, Application, Vertical and Region - Global Forecast to 2028

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:34.736178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c4ea57e2-03ca-4eb2-9d39-4b6250443368 · outbound

This paper cites Autonomous WiFi fingerprinting for indoor localization.

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices Autonomous WiFi fingerprinting for indoor localization

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:34.648354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 00d76555-baef-4d52-bb67-d95bd1cd31ac · outbound

This paper cites These methods enriched the training distribution and offered improved resilience to moderate noise.

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices These methods enriched the training distribution and offered improved resilience to moderate noise

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:25:34.865115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2b2dbdf5-e985-404b-bc87-224f9a8c025d · outbound

This paper cites On the Bottleneck of Graph Neural Networks and its Practical Implications.

GATE: Graph Attention Neural Networks with Real-Time Edge Construction for Robust Indoor Localization using Mobile Embedded Devices On the Bottleneck of Graph Neural Networks and its Practical Implications

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T17:25:34.079632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.