Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2503.19355.
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 2026-05-21T09:54:03.204081Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T09:54:05.592024Z
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 db5b8af1-ff61-44b0-a5ad-682e41cb3179 · inbound
4D-RGPT: Toward Region-level 4D Understanding via Perceptual Distillation cites this paper.
4D-RGPT: Toward Region-level 4D Understanding via Perceptual Distillation ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T21:21:16.869657Z
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 ed18f225-4ad3-4a64-a579-64ef0a22c88e · inbound
How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study cites this paper.
How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:00:53.436929Z
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 98e0b454-20d7-4bb3-a55d-b9be03ebe6f7 · inbound
How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study cites this paper.
How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T09:54:05.594049Z
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 21018879-d272-40f5-96ec-59373d4922c6 · inbound
PRISM: A Benchmark for Programmatic Spatial-Temporal Reasoning cites this paper.
PRISM: A Benchmark for Programmatic Spatial-Temporal Reasoning ST-VLM: Kinematic Instruction Tuning for Spatio-Temporal Reasoning in Vision-Language Models
Reference 20
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T05:53:04.328749Z
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.