Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.17016.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T23:56:32.408106Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-12T20:54:46.231340Z
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 480d9270-a253-4d6b-9c43-ebbb0b7aeacc · inbound
LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language Interpretation cites this paper.
LHRS-Bot-Nova: Improved Multimodal Large Language Model for Remote Sensing Vision-Language Interpretation On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications
Reference 19
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-12T20:54:46.238454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f7eba744-9f3f-493b-aa64-562bbcd046af · inbound
Geospatial Mechanistic Interpretability of Large Language Models cites this paper.
Geospatial Mechanistic Interpretability of Large Language Models On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T23:56:32.408106Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.