Paper Citation Record · LEDGER

DyMU: Dynamic Merging and Virtual Unmerging for Efficient VLMs

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2504.17040.

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

pith.paper-citation-record.v1
2504.17040 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 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:42:41.817259Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:48:56.484624Z

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 35cc6b1a-5102-42b5-89da-2fcb02b14972 · inbound

STAR: Stage-Wise Attention-Guided Token Reduction for Efficient Large Vision-Language Models Inference cites this paper.

STAR: Stage-Wise Attention-Guided Token Reduction for Efficient Large Vision-Language Models Inference DyMU: Dynamic Merging and Virtual Unmerging for Efficient VLMs

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T20:42:41.817259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e01b91bf-40c6-447d-b232-10bc0d6734ef · inbound

CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models cites this paper.

CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models DyMU: Dynamic Merging and Virtual Unmerging for Efficient VLMs

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:13:26.448577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 734c485a-6a92-4c5d-adf6-765f574d6b57 · inbound

RegimeVGGT: Layer-Wise Spatially Preserving Redundancy Removal for Visual Geometry Grounded Transformer cites this paper.

RegimeVGGT: Layer-Wise Spatially Preserving Redundancy Removal for Visual Geometry Grounded Transformer DyMU: Dynamic Merging and Virtual Unmerging for Efficient VLMs

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:48:56.486274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 22517f44-5ec4-418c-aa52-cf96dcdb49a2 · inbound

Attention-Free and Lightweight Token Reduction for Efficient Vision-Language Models cites this paper.

Attention-Free and Lightweight Token Reduction for Efficient Vision-Language Models DyMU: Dynamic Merging and Virtual Unmerging for Efficient VLMs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T05:03:27.729468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.