mlsanityData to 14 Oct 2026

CHECK-MAT: Checking Hand-Written Mathematical Answers for the Russian Unified State Exam

arXiv 2507.22958 ↗First posted 29 Jul 2025cs.CV cs.AI cs.LGcited by 2

On the map: Multimodal LLMs / vision-language models → VLM benchmarks and visual reasoning

Abstract (arXiv)

This paper introduces a novel benchmark, EGE-Math Solutions Assessment Benchmark, for evaluating Vision-Language Models (VLMs) on their ability to assess hand-written mathematical solutions. Unlike existing benchmarks that focus on problem solving, our approach centres on understanding student solutions, identifying mistakes, and assigning grades according to fixed criteria. We compile 122 scanned solutions from the Russian Unified State Exam (EGE) together with official expert grades, and evaluate seven modern VLMs from Google, OpenAI, Arcee AI, and Alibaba Cloud in three inference modes. The results reveal current limitations in mathematical reasoning and human-rubric alignment, opening new research avenues in AI-assisted assessment. You can find code in https://github.com/Karifannaa/Auto-check-EGE-math

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in VLM benchmarks and visual reasoning, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 3 of its 10 references that are in the map. First posted on arXiv 29 Jul 2025.

Builds on

3 of 10 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts3 Oct

Other references · 2

  1. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  2. 2021Measuring Mathematical Problem Solving With the MATH Datasetcited by 5,371

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025DOoM: Difficult Olympiads of Mathcited by 1
  2. 2026EDU-CIRCUIT-HW: Evaluating Multimodal Large Language Models on Real-World University-Level STEM Student Handwritten Solutionscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026The Aftermath of DrawEduMath: Vision Language Models Underperform with Struggling Students and Misdiagnose Errors
  2. 2025Can Vision-Language Models Evaluate Handwritten Math?
  3. 2025EEFSUVA: A New Mathematical Olympiad Benchmark
  4. 2025Mathematical Computation and Reasoning Errors by Large Language Models
  5. 2026When VLMs 'Fix' Students: Identifying and Penalizing Over-Correction in the Evaluation of Multi-line Handwritten Math OCR
  6. 2026Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark
  7. 2024DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models
  8. 2025VEHME: A Vision-Language Model For Evaluating Handwritten Mathematics Expressions