Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2311.11319.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:45:42.528919Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T18:23:51.047347Z
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 bb7b8ff2-30ad-449c-8c87-966dedec3bdf · inbound
fabSAM: A Farmland Boundary Delineation Method Based on the Segment Anything Model cites this paper.
fabSAM: A Farmland Boundary Delineation Method Based on the Segment Anything Model GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:12:07.582048Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 67a64a4f-b2cf-4e48-bf24-db705de2d512 · inbound
Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning cites this paper.
Online Location Planning for AI-Defined Vehicles: Optimizing Joint Tasks of Order Serving and Spatio-Temporal Heterogeneous Model Fine-Tuning GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:39:40.767276Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c69d258b-1905-4672-8169-3620b5e45690 · inbound
LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery cites this paper.
LISAT: Language-Instructed Segmentation Assistant for Satellite Imagery GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:45:42.528919Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9249c596-e176-49e3-9892-c6eaf6f9d219 · inbound
ShadeBench: A Benchmark Dataset for Building Shade Simulation in Sustainable Society cites this paper.
ShadeBench: A Benchmark Dataset for Building Shade Simulation in Sustainable Society GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T06:59:45.399055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation c06b9df0-c1cc-4366-b413-3bb991109cff · inbound
RoadGIE: Towards A Global-Scale Aerial Benchmark for Generalizable Interactive Road Extraction cites this paper.
RoadGIE: Towards A Global-Scale Aerial Benchmark for Generalizable Interactive Road Extraction GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T18:23:51.048875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation d9f51e70-acb9-43c0-a13c-7572cb29b2f5 · inbound
Evaluating Semantic and Spatial Guidance for Foundation Model Segmentation of Small-Scale PV in Remote Sensing Imagery cites this paper.
Evaluating Semantic and Spatial Guidance for Foundation Model Segmentation of Small-Scale PV in Remote Sensing Imagery GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T17:09:42.176933Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.