Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
RobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloud
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.11536.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T23:26:44.343668Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T01:42:23.512911Z
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 d3627082-cab5-410b-b78e-3f97377a78da · inbound
IMM-MOT: A Novel 3D Multi-object Tracking Framework with Interacting Multiple Model Filter cites this paper.
IMM-MOT: A Novel 3D Multi-object Tracking Framework with Interacting Multiple Model Filter RobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloud
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T23:26:44.343668Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7952dbea-a57a-40e4-bebd-def5d8fcfd38 · inbound
Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions cites this paper.
Trajectory Prediction for Autonomous Driving: Progress, Limitations, and Future Directions RobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloud
Reference 223
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T01:42:23.516438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 7d554643-4a3b-4f3c-b805-05059ec642e0 · inbound
Stable at Any Speed: Speed-Driven Multi-Object Tracking with Learnable Kalman Filtering cites this paper.
Stable at Any Speed: Speed-Driven Multi-Object Tracking with Learnable Kalman Filtering RobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloud
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T10:17:26.220900Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.