Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DisTime: Distribution-based Time Representation for Video Large Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2505.24329.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T05:14:24.814323Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T08:40:46.400243Z
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 48cf3857-f29c-42f7-8e63-d7dbd67fd0c2 · inbound
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation cites this paper.
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation DisTime: Distribution-based Time Representation for Video Large Language Models
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T08:40:46.401909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4944cbca-33ab-44b1-a708-1985c1e860aa · inbound
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation cites this paper.
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation DisTime: Distribution-based Time Representation for Video Large Language Models
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:14:24.814323Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f28223d-7405-4cd7-83c5-6a4824473fa1 · inbound
OmniVTG: A Large-Scale Dataset and Training Paradigm for Open-World Video Temporal Grounding cites this paper.
OmniVTG: A Large-Scale Dataset and Training Paradigm for Open-World Video Temporal Grounding DisTime: Distribution-based Time Representation for Video Large Language Models
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:31:15.758838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fb0229f2-85fa-4610-ba82-d25d5f94f700 · inbound
TimePLE: Rethinking Temporal Representation for Video Temporal Grounding cites this paper.
TimePLE: Rethinking Temporal Representation for Video Temporal Grounding DisTime: Distribution-based Time Representation for Video Large Language Models
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:32:54.788326Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.