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Paper Citation Record · LEDGER

Video Token Merging for Long-form Video Understanding

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.23782.

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

pith.paper-citation-record.v1
2410.23782 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:29:51.350310Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:48:56.496339Z

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 1859956c-fa26-4f03-acbe-d34f0e8363e9 · inbound

AuroraLong: Bringing RNNs Back to Efficient Open-Ended Video Understanding cites this paper.

AuroraLong: Bringing RNNs Back to Efficient Open-Ended Video Understanding Video Token Merging for Long-form Video Understanding

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T20:29:51.350310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:29:51.350310Z digest=sha256:d483cc065973df0db8bfd17a5013ea46e4fc77ff57fc5f664377c2149a31c38b

Observation d79cec4c-a41e-41c4-b4c1-8297fe08f7af · inbound

FastVGGT: Training-Free Acceleration of Visual Geometry Transformer cites this paper.

FastVGGT: Training-Free Acceleration of Visual Geometry Transformer Video Token Merging for Long-form Video Understanding

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-15T23:36:06.948609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T23:36:06.870759Z digest=sha256:be8046cf95ad076d7e54fa576f2fb4e3a369e9651f81d398abc6e4ee3da85673

Observation 4f2718b1-0fff-4868-bd07-d9404128d3b1 · inbound

LongVideo-R1: Smart Navigation for Low-cost Long Video Understanding cites this paper.

LongVideo-R1: Smart Navigation for Low-cost Long Video Understanding Video Token Merging for Long-form Video Understanding

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:01:33.388166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T20:01:31.129959Z digest=sha256:01c4766578aa3a86678af1776146df37fa624a2d5512319e2ae06a824606f89d

Observation 09d11998-5a94-449e-b49f-30d9049459f3 · 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 Video Token Merging for Long-form Video Understanding

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-03T20:48:56.497813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T01:07:08.415112Z digest=sha256:925c9c17275b464cc7d33963e1a21f4128bdf1ea86b3922980adb4531e0c91b2

Observation 48d86d1c-a1b4-44a3-a713-47a48858a4f7 · inbound

Fast Enough to Act: Spatio-Temporal Visual Token Merging for Low-Latency Robotic VLMs and VLAs cites this paper.

Fast Enough to Act: Spatio-Temporal Visual Token Merging for Low-Latency Robotic VLMs and VLAs Video Token Merging for Long-form Video Understanding

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-30T07:34:22.136566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T07:24:59.159037Z digest=sha256:e3309c301df120ba35a6f617cc4a969426ae3ea4e55cb2ade1e3d629fa2a1d9b