Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T12:13:34.530858Z
Paper Citation Record · LEDGER
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps
As of 17 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2411.17425.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
13 of 13 outbound references displayed
- verified exact0
- verified fuzzy11
- unresolved2
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f2e30d17-0222-4eca-8c01-96c21ae226bf · outbound
This paper cites Mask2Former for Video Instance Segmentation.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Mask2Former for Video Instance Segmentation
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:13:34.464324Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d5af1e69-f5ba-4234-b377-283cff84e373 · outbound
This paper cites Schwing, Alexander Kirillov, and Rohit Gird- har.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Schwing, Alexander Kirillov, and Rohit Gird- har
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:35.090984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d6e6919f-2679-4bd4-89ee-c9c5d3b6af06 · outbound
This paper cites Querying historical maps as a unified, structured, and linked spatiotemporal source.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Querying historical maps as a unified, structured, and linked spatiotemporal source
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:35.024910Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 47247b35-b282-44e4-a574-b0ed6803d5a9 · outbound
This paper cites Approximate topological relations.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Approximate topological relations
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:35.011278Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation dfa06c7a-6932-459c-9b16-7ee0d154a766 · outbound
This paper cites Mask R-CNN.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Mask R-CNN
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.997349Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fefddc77-8f0f-411d-af7f-44baa18e8b0a · outbound
This paper cites Unlocking the Geospatial Past with Deep Learning – Establishing a Hub for Historical Map Data in Switzerland.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Unlocking the Geospatial Past with Deep Learning – Establishing a Hub for Historical Map Data in Switzerland
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.985506Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5fddee48-d079-4baa-8e80-36323c895f38 · outbound
This paper cites Lawrence Zitnick, and Piotr Dollár.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Lawrence Zitnick, and Piotr Dollár
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:13:34.507728Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c00e0022-5a53-49ae-8ba5-a26fe9fe22c1 · outbound
This paper cites Aligning geographic entities from historical maps for building knowledge graphs.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Aligning geographic entities from historical maps for building knowledge graphs
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.952792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 28f7a82a-d7ff-48c6-a620-109670e8cd2e · outbound
This paper cites Videocutler: Surprisingly simple unsupervised video instance segmentation, 2023.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Videocutler: Surprisingly simple unsupervised video instance segmentation, 2023
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.904788Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f14f77d4-32da-4d1c-8d0f-bd07b2f0aee1 · outbound
This paper cites Contrastive Pretraining for Railway Detection: Unveiling Historical Maps with Transformers.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Contrastive Pretraining for Railway Detection: Unveiling Historical Maps with Transformers
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.835986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5205370d-009f-4d73-befb-dc4085b8231d · outbound
This paper cites Segmenting Moving Objects via an Object- Centric Layered Representation.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Segmenting Moving Objects via an Object- Centric Layered Representation
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.714266Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9b902422-a566-4774-b3ed-a454662819cf · outbound
This paper cites Self-supervised Video Object Segmentation by Motion Grouping.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps Self-supervised Video Object Segmentation by Motion Grouping
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.598334Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation da90655c-8ccc-4928-a1c4-71e2364ca60b · outbound
This paper cites approximately within.
Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps approximately within
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T12:13:34.575161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.