Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.09447.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T19:24:43.064984Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T07:44:02.803718Z
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 5eaca39b-0d06-451d-85de-b412a0d46603 · inbound
How to Merge Your Multimodal Models Over Time? cites this paper.
How to Merge Your Multimodal Models Over Time? kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T19:24:43.064984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c5ac5392-ae9e-460f-a0c7-98e8065b942e · inbound
Learning Yourself: Class-Incremental Semantic Segmentation with Language-Inspired Bootstrapped Disentanglement cites this paper.
Learning Yourself: Class-Incremental Semantic Segmentation with Language-Inspired Bootstrapped Disentanglement kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:37:14.906434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 535e44c7-29a2-4dfc-8f87-1a2c2908eb7f · inbound
SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation cites this paper.
SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:53:19.817007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 8fe7aaaa-72cd-4520-862c-708782358f19 · inbound
SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation cites this paper.
SegRAG: Training-Free Retrieval-Augmented Semantic Segmentation kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T07:44:02.804933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d827865e-52ac-46af-a809-b1cf836b1892 · inbound
SCI-CLIP: Segment-Centric Inference with Reference Memory for Training-Free Open-Vocabulary Segmentation cites this paper.
SCI-CLIP: Segment-Centric Inference with Reference Memory for Training-Free Open-Vocabulary Segmentation kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T01:06:06.520994Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.