Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Unsupervised Path Representation Learning with Curriculum Negative Sampling
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2106.09373.
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 2026-08-12T04:54:41.057671Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T06:38:05.728713Z
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 66f9dc0c-2cbc-41a0-ab2c-5bb926f38370 · inbound
BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis cites this paper.
BIGCity: A Universal Spatiotemporal Model for Unified Trajectory and Traffic State Data Analysis Unsupervised Path Representation Learning with Curriculum Negative Sampling
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T04:54:41.057671Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c73ca74b-9ff2-44ec-ab00-5c05abd1c32f · inbound
STAHGNet: Modeling Hybrid-grained Heterogenous Dependency Efficiently for Traffic Prediction cites this paper.
STAHGNet: Modeling Hybrid-grained Heterogenous Dependency Efficiently for Traffic Prediction Unsupervised Path Representation Learning with Curriculum Negative Sampling
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:31:34.746140Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 387b728d-1bd1-4760-b193-85fec1b5c303 · inbound
TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning cites this paper.
TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning Unsupervised Path Representation Learning with Curriculum Negative Sampling
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T06:38:05.730546Z
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.