Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2306.13092.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:59:04.118690Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T14:07:02.384303Z
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 a0944248-4c16-4dc6-8729-1a0cff764c0c · inbound
Approximating Language Model Training Data from Weights cites this paper.
Approximating Language Model Training Data from Weights Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:59:04.118690Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d604cecb-090f-44e0-97e1-da48e3d5455f · inbound
Multimodal Distribution Matching for Vision-Language Dataset Distillation cites this paper.
Multimodal Distribution Matching for Vision-Language Dataset Distillation Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
Reference 71
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T04:30:19.718376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 5bd5d8d5-03fc-46bc-83db-2e0aa7e37d07 · inbound
Condensing Large-Scale Datasets Directly with Minimal Information Loss cites this paper.
Condensing Large-Scale Datasets Directly with Minimal Information Loss Squeeze, Recover and Relabel: Dataset Condensation at ImageNet Scale From A New Perspective
Reference 49
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T14:07:02.385572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.