Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.20363.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:16:46.578084Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T23:06:20.227988Z
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 e3e2c3a1-9f02-401a-b925-f5da66821965 · inbound
GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization cites this paper.
GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:16:46.578084Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d4924ea-d352-464b-acdf-89e9a5626bd3 · inbound
From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models cites this paper.
From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T23:50:47.226375Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 58e0159d-7fa9-45e5-bbc2-32cec3d357e0 · inbound
Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View cites this paper.
Do VLMs See What Sensors Feel? A Scalable Expert-Guided Design for Wheelchair Accessibility Assessment from Street View LLMGeo: Benchmarking Large Language Models on Image Geolocation In-the-wild
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T23:06:20.230133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.