Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.15286.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T23:47:40.687529Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T22:45:20.059889Z
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 aa0fe25e-e516-4378-ae10-c6716e304b8f · inbound
Causal Prompt Calibration Guided Segment Anything Model for Open-Vocabulary Multi-Entity Segmentation cites this paper.
Causal Prompt Calibration Guided Segment Anything Model for Open-Vocabulary Multi-Entity Segmentation 3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T22:45:20.067157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9efecbca-0a74-4f71-b833-06bc3001c743 · inbound
SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation cites this paper.
SELECT: A Submodular Approach for Active LiDAR Semantic Segmentation 3D Annotation-Free Learning by Distilling 2D Open-Vocabulary Segmentation Models for Autonomous Driving
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T23:47:40.687529Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.