Paper Citation Record · LEDGER

UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2502.06474.

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

pith.paper-citation-record.v1
2502.06474 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 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:53:24.588515Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T15:34:48.324415Z

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 abbcd6f8-fb9e-4226-bd62-53b52b9d3f5c · inbound

UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning cites this paper.

UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T12:53:24.588515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58fe0e7f-27ae-411e-a5af-684a1867b2ce · inbound

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models cites this paper.

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:42:21.515237Z

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 26e843a3-6b1e-45bc-9c71-5c2a53ef71b9 · inbound

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models cites this paper.

G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:57:40.364921Z

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 40948551-860f-41bc-9405-333c4030406e · inbound

Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey cites this paper.

Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey UniMoD: Efficient Unified Multimodal Transformers with Mixture-of-Depths

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:34:48.325959Z

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.