Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.14504.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:42:53.680275Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:38:46.491544Z
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 ef92b47f-c261-402f-b269-3b1485509843 · inbound
GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models cites this paper.
GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:42:53.680275Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33b96bcb-d5e4-49bb-993f-60a4551697d4 · inbound
EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent cites this paper.
EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T15:38:46.573996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.