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Paper Citation Record · LEDGER

MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.07529.

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

pith.paper-citation-record.v1
2401.07529 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:56:13.084754Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T18:44:28.884400Z

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 c6838485-6b2c-4ede-bb90-d3c423c6922f · inbound

LLM Evaluators Recognize and Favor Their Own Generations cites this paper.

LLM Evaluators Recognize and Favor Their Own Generations MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-22T18:44:28.886552Z

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.

source=pdf_text observed=2026-05-22T18:44:28.766639Z digest=sha256:c193705bf9d743250a7fabc1eb81b10e20ec32a29c239de03130893f0324efdf

Observation d9326e9f-758e-4ab4-a6ac-503726f9766b · inbound

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches cites this paper.

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception

Reference 267

Resolution
unresolved
no resolver link, observed 2026-08-10T21:56:13.084754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:13.084754Z digest=sha256:d75fe06f87830fb081454abf5a2d83565df7afa0a22c42edd9cf4ce099af6ef8

Observation 8a31af75-9e2f-4a15-b300-812764768463 · inbound

Can Multimodal Large Language Models Truly Understand Small Objects? cites this paper.

Can Multimodal Large Language Models Truly Understand Small Objects? MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:01:19.426858Z

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.

source=pdf_text observed=2026-05-08T12:49:53.645987Z digest=sha256:a0664cf63e2e8af8434fca1c36ccffd132499b0fd0cec08fed5e0b3fdd1a6db2