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Paper Citation Record · LEDGER

MMR: Evaluating Reading Ability of Large Multimodal Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.14594.

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

pith.paper-citation-record.v1
2408.14594 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:57:07.432546Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:10:08.824806Z

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 1bdd0ad0-d2cc-4fb0-9f03-9aee76356e82 · inbound

MusiXQA: Advancing Visual Music Understanding in Multimodal Large Language Models cites this paper.

MusiXQA: Advancing Visual Music Understanding in Multimodal Large Language Models MMR: Evaluating Reading Ability of Large Multimodal Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T21:57:07.432546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:57:07.432546Z digest=sha256:102dfb79346effead20f9a05ac795fb2fafd70f351c3952caa8ef5929a933391

Observation 17ee1c91-bd37-4bdd-b3c7-811c5e3a18e8 · inbound

VisR-Bench: An Empirical Study on Visual Retrieval-Augmented Generation for Multilingual Long Document Understanding cites this paper.

VisR-Bench: An Empirical Study on Visual Retrieval-Augmented Generation for Multilingual Long Document Understanding MMR: Evaluating Reading Ability of Large Multimodal Models

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-08-05T22:10:08.828773Z

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.

source=pdf_text observed=2026-08-05T22:10:08.089589Z digest=sha256:a597d0957796b03573e3d86aaccefb5e1f636ae9570e4d05ba6029a864f7555a