Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.10265.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T10:21:50.279366Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:48:02.763503Z
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 e3a77be0-34d3-4400-893f-ddb5acf4f3c4 · inbound
gen2seg: Generative Models Enable Generalizable Instance Segmentation cites this paper.
gen2seg: Generative Models Enable Generalizable Instance Segmentation ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T14:31:40.552717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b1bf4cf7-f9b0-4423-a81f-43ac58a34529 · inbound
Formalizing the Binding Problem cites this paper.
Formalizing the Binding Problem ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
Reference 104
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T03:06:29.839233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d420bf98-f25d-470e-ba9d-bd4bde004430 · inbound
Dual-State Slot Attention: Decoupling Appearance and Identity for Video Object-Centric Learning cites this paper.
Dual-State Slot Attention: Decoupling Appearance and Identity for Video Object-Centric Learning ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:48:02.765579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.