Paper Citation Record · LEDGER

Wolf: Dense Video Captioning with a World Summarization Framework

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2407.18908.

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

pith.paper-citation-record.v1
2407.18908 v2

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 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:55:58.410638Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T17:23:44.936349Z

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 371880b3-982f-47c9-9921-f304e7dd12b5 · inbound

Progress-Aware Video Frame Captioning cites this paper.

Progress-Aware Video Frame Captioning Wolf: Dense Video Captioning with a World Summarization Framework

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T23:55:58.410638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58441840-3484-4038-bb12-319dac818766 · inbound

MVTamperBench: Evaluating Robustness of Vision-Language Models cites this paper.

MVTamperBench: Evaluating Robustness of Vision-Language Models Wolf: Dense Video Captioning with a World Summarization Framework

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T23:55:17.555813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 298b7980-dea8-4297-8be3-aca7894a6bb8 · inbound

MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models cites this paper.

MASS: Motion-Aware Spatial-Temporal Grounding for Physics Reasoning and Comprehension in Vision-Language Models Wolf: Dense Video Captioning with a World Summarization Framework

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-17T05:59:08.717796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9f0d7d01-72f0-4063-90af-4daa7239d4d5 · inbound

FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies cites this paper.

FineVLA: Fine-Grained Instruction Alignment for Steerable Vision-Language-Action Policies Wolf: Dense Video Captioning with a World Summarization Framework

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-29T17:23:44.937908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.