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Paper Citation Record · LEDGER

MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models

As of 18 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 1 inbound Pith citation observation for arXiv:2508.13938.

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

pith.paper-citation-record.v1
2508.13938 v1

Coverage vector

measured 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:53:05.214761Z

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:12:45.523967Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T18:12:46.678251Z

Reference resolution

4 of 4 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7464e93f-84fc-44e9-a514-0b3aa0c65612 · outbound

This paper cites PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models.

MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-05T18:53:05.114132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:53:05.114132Z digest=sha256:e2d5070b8708a897adacdc250f9eda848149dc86a861366c6a646cd379762ee8

Observation dac95634-5e48-4fae-897d-b95e50e70bcc · outbound

This paper cites Evaluating the Performance of Large Language Models on GAOKAO Benchmark.

MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-05T18:53:05.214761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:53:05.214761Z digest=sha256:e6b2b76cb5cedb1dca7694ab56ed4d6d59f352b8a08f9c13a4e96bbe3be2c867

Observation 84f8d49f-094c-4fea-85e1-5baa35d2c0d5 · outbound

This paper cites A Survey on LLM-as-a-Judge.

MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models A Survey on LLM-as-a-Judge

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-05T18:53:04.972885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:53:04.972885Z digest=sha256:a88df01a888f9c472f4aa89bb772e1719f2bff801693562184410e08c521725f

Observation e2498c15-1ae6-4456-91ac-4b9828478eed · outbound

This paper cites R-Bench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation.

MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models R-Bench: Graduate-level Multi-disciplinary Benchmarks for LLM & MLLM Complex Reasoning Evaluation

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-05T18:53:05.031094Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:53:05.031094Z digest=sha256:e3d23f22f00466ebefce00315c1be27c7a570e66bb58e504e03c609802b582da

Pith citing papers

Observation 4e4767a2-f4f0-40e0-856d-c10dc52e55f6 · inbound

Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery cites this paper.

Science Edge Evaluation: SEE the Missing Step Toward Real Scientific Discovery MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models

Reference 15

Resolution
metadata mismatch
local_arxiv, observed 2026-08-10T18:12:46.684001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-10T18:12:45.523967Z digest=sha256:66fb8a29cc51bbab9fc64466c7ce5f9fe187684c2266d4d0128ac415fdb6ae8f