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Paper Citation Record · LEDGER

From Image to Video, what do we need in multimodal LLMs?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.11865.

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

pith.paper-citation-record.v1
2404.11865 v2

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:59:16.278173Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T10:46:28.841591Z

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 37346644-d986-4f15-b3e8-8b16ae9b83ad · inbound

InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output cites this paper.

InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output From Image to Video, what do we need in multimodal LLMs?

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-17T10:46:28.844476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-17T10:46:28.447347Z digest=sha256:c23fa3258eef776937a768383776937a3f835f1b3d2c5e0f0e1b72e3ea0063f9

Observation 8faf21c6-a3bf-4ade-a893-cd6fe75dedf0 · inbound

Iterative Zoom-In: Temporal Interval Exploration for Long Video Understanding cites this paper.

Iterative Zoom-In: Temporal Interval Exploration for Long Video Understanding From Image to Video, what do we need in multimodal LLMs?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T21:59:16.278173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:59:16.278173Z digest=sha256:168597cd8dcf5b16175cd65ce4a194e7f6d6e441253412cbbeb7e712726fd454

Observation e91e360f-fa3d-4e3a-9f10-46365cf7bf7a · inbound

Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey cites this paper.

Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey From Image to Video, what do we need in multimodal LLMs?

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:30:57.210561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:36:33.264166Z digest=sha256:1c94400449d0a61b9ce54abe3598f85d184f0e2392cc26a5a57596ba5b30c3f8

Observation 7dd0a2ad-7068-4bb3-a3dc-a6079849cc68 · inbound

Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey cites this paper.

Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey From Image to Video, what do we need in multimodal LLMs?

Reference 78

Resolution
unresolved
no resolver link, observed 2026-07-12T22:04:31.302192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T22:04:31.302192Z digest=sha256:5039ae150d5ec0d679b10a7fd774a39a664c0a09ee98ed4b9b985ea9dd24aaf4

Observation 7b6213fe-f6f5-45d9-b980-2e18b71f873f · inbound

One Token per Highly Selective Frame: Towards Extreme Compression for Long Video Understanding cites this paper.

One Token per Highly Selective Frame: Towards Extreme Compression for Long Video Understanding From Image to Video, what do we need in multimodal LLMs?

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:30:26.543737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T13:28:58.920442Z digest=sha256:7d3df6a569fc786e15be4af8706dd1c27a1a31be6caec2c4720f27df2ce09496