Paper Citation Record · LEDGER

ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2504.18152.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2504.18152 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T09:46:56.063333Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T09:54:35.322765Z

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 f50d51cd-1905-4ed7-b73f-622651c3aa42 · inbound

SVAgent: Storyline-Guided Long Video Understanding via Cross-Modal Multi-Agent Collaboration cites this paper.

SVAgent: Storyline-Guided Long Video Understanding via Cross-Modal Multi-Agent Collaboration ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:00:49.056011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 690280ac-a2d5-4e5b-b0dc-d60ab562d5e4 · inbound

Mining Multi-Modality Spatio-Temporal Cues for Video Important Person Identification cites this paper.

Mining Multi-Modality Spatio-Temporal Cues for Video Important Person Identification ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:33:28.320458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 251ad567-e0b9-480a-9e46-e318d7da0ca8 · inbound

HumanMoveVQA: Can Video MLLMs reason about human movement in videos? cites this paper.

HumanMoveVQA: Can Video MLLMs reason about human movement in videos? ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:13:53.056250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b58fd2bb-2e51-4fd0-a17a-1a51846e9090 · inbound

HumanMoveVQA: Can Video MLLMs reason about human movement in videos? cites this paper.

HumanMoveVQA: Can Video MLLMs reason about human movement in videos? ActionArt: Advancing Multimodal Large Models for Fine-Grained Human-Centric Video Understanding

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-30T09:54:35.324230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.