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Paper Citation Record · LEDGER

Advancing Egocentric Video Question Answering with Multimodal Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2504.04550.

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

pith.paper-citation-record.v1
2504.04550 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 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:17:17.405246Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T23:19:02.831705Z

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 774a6b2c-af99-406f-9b2f-ea360eb6f438 · inbound

EASG-Bench: Video Q&A Benchmark with Egocentric Action Scene Graphs cites this paper.

EASG-Bench: Video Q&A Benchmark with Egocentric Action Scene Graphs Advancing Egocentric Video Question Answering with Multimodal Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T10:17:17.405246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:17:17.405246Z digest=sha256:15d62eedf09e20c3a58c90aaec5c270a404932e889aa9ca644dc20e947ee712e

Observation a80980e7-0192-4524-a0ef-2b0480689392 · inbound

Decoding Pedestrian Crossing Intention from Egocentric Vision via Vision Language Models cites this paper.

Decoding Pedestrian Crossing Intention from Egocentric Vision via Vision Language Models Advancing Egocentric Video Question Answering with Multimodal Large Language Models

Reference 52

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T00:27:29.683514Z

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=2026-06-27T17:13:04.236686Z digest=sha256:3371bd416d06c44551263d57cdbd729f734b1d217cdcf680312d95e6b0bf2fe8

Observation 232806af-3369-49e0-b036-ebf3aad66e44 · inbound

Rethinking RAG in Long Videos: What to Retrieve and How to Use It? cites this paper.

Rethinking RAG in Long Videos: What to Retrieve and How to Use It? Advancing Egocentric Video Question Answering with Multimodal Large Language Models

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-07-03T15:28:33.955737Z

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=2026-06-27T06:30:33.428489Z digest=sha256:337d4d88d047509a72515e197e1057ede14c9143595bcd0cab5077be90afd6c8

Observation cc847705-499d-4a27-a175-4d39eaadd2f1 · inbound

Graph it first! Enabling Reasoning on Long-form Egocentric Videos through Scene Graphs cites this paper.

Graph it first! Enabling Reasoning on Long-form Egocentric Videos through Scene Graphs Advancing Egocentric Video Question Answering with Multimodal Large Language Models

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-03T23:19:02.834424Z

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=2026-07-03T23:09:01.340759Z digest=sha256:c27bdb764352ae9a30a3e00efe8d69f9e6b0b821802cb93e09c24ac995559f1f