Paper Citation Record · LEDGER

15M Multimodal Facial Image-Text Dataset

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2407.08515.

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

pith.paper-citation-record.v1
2407.08515 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 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:07:27.621712Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T21:17:24.132233Z

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 f3cd8071-a568-4027-827a-498bba347186 · inbound

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling cites this paper.

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling 15M Multimodal Facial Image-Text Dataset

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:23:57.868217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c1535cd7-1311-4ab3-a765-abb76371da81 · inbound

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions cites this paper.

Learning Transferable Facial Emotion Representations from Large-Scale Semantically Rich Captions 15M Multimodal Facial Image-Text Dataset

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-06T13:07:27.621712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35bb7062-d70c-405c-9e8e-dc7506934447 · inbound

DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models 15M Multimodal Facial Image-Text Dataset

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:45:47.668216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 99c1a564-1d17-4dd2-82c3-b3b2f517d658 · inbound

DataComp-VLM: Improved Open Datasets for Vision-Language Models cites this paper.

DataComp-VLM: Improved Open Datasets for Vision-Language Models 15M Multimodal Facial Image-Text Dataset

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:17:24.134239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.