Paper Citation Record · LEDGER

CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2401.14011.

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

pith.paper-citation-record.v1
2401.14011 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:13:36.873714Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T08:03:13.744710Z

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 afc6ffdf-2f90-4c99-9de8-680fd9e1e13c · inbound

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection cites this paper.

ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-23T20:13:25.003350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ce2ccae2-ded4-4c57-aa91-3adc6d840ad1 · inbound

MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs cites this paper.

MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T14:31:36.937441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f32908a0-4a9c-4012-87c6-686eefd430da · inbound

RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? cites this paper.

RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems? CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T18:30:56.659553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5880b332-0ed5-4872-b79c-90421489126f · inbound

UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models cites this paper.

UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T15:40:39.658649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa3836ec-2b8b-4b11-8bdc-d4b2f41e389b · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:32:32.653833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8059e091-9fd4-45f9-a8cb-c97e28baca0f · inbound

Exploring Implicit Visual Misunderstandings in Multimodal Large Language Models through Attention Analysis cites this paper.

Exploring Implicit Visual Misunderstandings in Multimodal Large Language Models through Attention Analysis CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T21:13:36.873714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95a4f9f4-96cc-4e33-9af1-591cddb241f5 · inbound

AutoJudger: An Agent-Driven Framework for Efficient Benchmarking of MLLMs cites this paper.

AutoJudger: An Agent-Driven Framework for Efficient Benchmarking of MLLMs CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-07T13:40:20.204272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92a1694d-103f-4fb7-b5a7-cc87f020c4d2 · inbound

K12Vista: Exploring the Boundaries of MLLMs in K-12 Education cites this paper.

K12Vista: Exploring the Boundaries of MLLMs in K-12 Education CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:42:30.998921Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21bf0466-ab64-4011-8ceb-f8a4e23fc6a2 · inbound

Argus Inspection: Do Multimodal Large Language Models Possess the Eye of Panoptes? cites this paper.

Argus Inspection: Do Multimodal Large Language Models Possess the Eye of Panoptes? CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T11:18:57.951578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59c29797-7406-4cc9-8f12-44a690f1425f · inbound

BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset cites this paper.

BMMR: A Large-Scale Bilingual Multimodal Multi-Discipline Reasoning Dataset CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T20:15:52.706978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bac2a1ca-74bb-4ec4-8c82-b82999d6fe1e · inbound

EduFlow: Advancing MLLMs' Problem-Solving Proficiency through Multi-Stage, Multi-Perspective Critique cites this paper.

EduFlow: Advancing MLLMs' Problem-Solving Proficiency through Multi-Stage, Multi-Perspective Critique CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T18:04:53.550752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9f05df8-0e70-48a9-8651-492410c26098 · inbound

CArtBench: Evaluating Vision-Language Models on Chinese Art Understanding, Interpretation, and Authenticity cites this paper.

CArtBench: Evaluating Vision-Language Models on Chinese Art Understanding, Interpretation, and Authenticity CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T10:41:05.680332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 8c671f59-f69e-4ccd-81e6-7c782745768d · inbound

CArtBench: Evaluating Vision-Language Models on Chinese Art Understanding, Interpretation, and Authenticity cites this paper.

CArtBench: Evaluating Vision-Language Models on Chinese Art Understanding, Interpretation, and Authenticity CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-12T21:49:22.179834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91760f51-0e34-4d26-aa70-c36069bb9007 · inbound

Benchmarking Large Vision-Language Models on CFMME: A Comprehensive Chinese Financial Multimodal Evaluation Dataset cites this paper.

Benchmarking Large Vision-Language Models on CFMME: A Comprehensive Chinese Financial Multimodal Evaluation Dataset CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T08:03:13.746355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5dfe24a5-50af-4edb-bef3-34ab367b2a25 · inbound

SciExplore: Evaluating Autonomous Agents from Scientific Navigation to Information Integration cites this paper.

SciExplore: Evaluating Autonomous Agents from Scientific Navigation to Information Integration CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-01T09:00:57.661324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.