Paper Citation Record · LEDGER

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models

As of 21 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2507.03056.

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

pith.paper-citation-record.v1
2507.03056 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:31:28.738720Z

measured 39 of 39 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-16T11:30:30.116574Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-16T11:30:53.078257Z

Reference resolution

38 of 38 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6fdac771-4e73-445d-87bb-06e1d453225f · outbound

This paper cites Knowledge tracing: Modeling the acquisition of procedural knowledge,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Knowledge tracing: Modeling the acquisition of procedural knowledge,

Reference 1

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Observation 40aec8c0-d1cb-4f52-adc4-58136348da56 · outbound

This paper cites Caa of short non-mcq answers,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Caa of short non-mcq answers,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:31:29.059784Z

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Observation 7ac4cf5f-4bd1-4c1a-b8b1-2a6a34b53686 · outbound

This paper cites Effective feature in- tegration for automated short answer scoring,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Effective feature in- tegration for automated short answer scoring,

Reference 3

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This paper cites Vector based techniques for short answer grading,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Vector based techniques for short answer grading,

Reference 4

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Observation 93d14ef2-580a-431e-9be8-50796593932e · outbound

This paper cites An automatic short-answer grading model for semi-open-ended questions,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models An automatic short-answer grading model for semi-open-ended questions,

Reference 5

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Observation e8766c50-8859-466a-8730-67f9961bc9c7 · outbound

This paper cites The automated grading of student open responses in mathe- matics,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models The automated grading of student open responses in mathe- matics,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:31:29.019653Z

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Observation 7d2fb077-c1ca-4c5b-b8d0-5975511fcce0 · outbound

This paper cites Mathematical language processing: Automatic grading and feedback for open response mathematical questions,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Mathematical language processing: Automatic grading and feedback for open response mathematical questions,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:31:29.009961Z

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Observation f478cee6-2741-4640-ab50-6de6b766205a · outbound

This paper cites Efficient estimation of word representations in vector space,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Efficient estimation of word representations in vector space,

Reference 8

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Observation b4a1fa13-8005-4a32-ba26-711083a7db86 · outbound

This paper cites Glove: Global vectors for word representation,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Glove: Global vectors for word representation,

Reference 9

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Observation f59aab36-6390-4831-8779-51d2d3035c6b · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 10

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Observation 777cd7a1-0de9-4038-8198-69a49751d790 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 11

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Observation b2e94104-cc72-4437-9e7e-00cf83cff743 · outbound

This paper cites Pre-training bert on domain resources for short answer grading,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Pre-training bert on domain resources for short answer grading,

Reference 12

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Observation 103fa61c-b8dc-4e3b-b291-80e157bcfe2e · outbound

This paper cites Exploring automatic short answer grading as a tool to assist in human rating,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Exploring automatic short answer grading as a tool to assist in human rating,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:31:28.974348Z

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Observation e4e6b423-1630-4905-86f4-92bbfd8a9abf · outbound

This paper cites Improving automated scoring of student open responses in mathematics.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Improving automated scoring of student open responses in mathematics

Reference 14

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Observation f412a33c-2fcd-4624-9da4-7027ab445f13 · outbound

This paper cites MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models MathBERT: A Pre-trained Language Model for General NLP Tasks in Mathematics Education

Reference 15

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Observation 01069d4f-5bb4-43a3-b2f7-d6a1332f4e09 · outbound

This paper cites A detailed analysis of optical character recognition technology,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models A detailed analysis of optical character recognition technology,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:31:28.956441Z

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Observation c5ceb5d3-fa1b-46dc-9f0b-c0a8901dd87b · outbound

This paper cites Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Watch, attend and parse: An end-to-end neural network based approach to handwritten mathematical expression recognition,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:31:28.947269Z

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Observation 8d7fdf1f-cdad-4cb5-8d33-061938ec1b08 · outbound

This paper cites Track, attend, and parse (tap): An end-to-end framework for online handwritten mathematical expression recognition,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Track, attend, and parse (tap): An end-to-end framework for online handwritten mathematical expression recognition,

Reference 18

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Observation aecd21e8-7982-4b36-b437-2acc7ad38d5a · outbound

This paper cites AI-assisted Automated Short Answer Grading of Handwritten University Level Mathematics Exams.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models AI-assisted Automated Short Answer Grading of Handwritten University Level Mathematics Exams

Reference 19

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Observation 14bec6b8-1f69-4593-bf7a-cd93203b369d · outbound

This paper cites Toward ai grading of student problem solutions in introductory physics: A feasibility study,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Toward ai grading of student problem solutions in introductory physics: A feasibility study,

Reference 20

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Observation 71dc8679-6144-4d0a-aabf-ba327858a408 · outbound

This paper cites DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students' Hand-Drawn Math Images.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students' Hand-Drawn Math Images

Reference 21

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Observation 8b73c33f-3317-48b3-b84c-5e2d70b4bf27 · outbound

This paper cites Auto-scoring student responses with images in mathematics.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Auto-scoring student responses with images in mathematics

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:31:28.920068Z

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Observation e06786e6-f7eb-4369-af52-23bc1eb73401 · outbound

This paper cites Sympy: symbolic computing in python,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Sympy: symbolic computing in python,

Reference 23

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Observation de27fe5c-fae5-4914-9f5f-c98f858f4e2c · outbound

This paper cites Automatic Short Math Answer Grading via In-context Meta-learning.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Automatic Short Math Answer Grading via In-context Meta-learning

Reference 24

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Observation 64235af8-9aec-4868-8105-9e87026ecf58 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Learning transferable visual models from natural language supervision,

Reference 25

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Observation f0e0085b-f9ba-48bb-a0ee-b3983b722ccb · outbound

This paper cites Evaluating GPT-4 at Grading Handwritten Solutions in Math Exams.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Evaluating GPT-4 at Grading Handwritten Solutions in Math Exams

Reference 26

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This paper cites The assistments ecosystem: Building a platform that brings scientists and teachers together for min- imally invasive research on human learning and teaching,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models The assistments ecosystem: Building a platform that brings scientists and teachers together for min- imally invasive research on human learning and teaching,

Reference 27

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Observation a4d8adaa-b24d-4e86-beb1-c53ca9126357 · outbound

This paper cites An overview of the tesseract ocr engine,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models An overview of the tesseract ocr engine,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Imagenet classification with deep convolutional neural networks,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Visualizing and understanding convo- lutional networks,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Very deep convolutional networks for large-scale image recognition,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Going deeper with convolutions,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Deep residual learning for image recognition,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Matching net- works for one shot learning,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Prototypical networks for few-shot learning,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Learning to compare: Relation network for few-shot learning,

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Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Model-agnostic meta-learning for fast adaptation of deep networks,

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This paper cites Meta-dataset: A dataset of datasets for learning to learn from few examples,.

Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models Meta-dataset: A dataset of datasets for learning to learn from few examples,

Reference 38

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Pith citing papers

Observation 52b4ff20-deda-4d18-a203-aa39de34e0f1 · inbound

EDU-CIRCUIT-HW: Evaluating Multimodal Large Language Models on Real-World University-Level STEM Student Handwritten Solutions cites this paper.

EDU-CIRCUIT-HW: Evaluating Multimodal Large Language Models on Real-World University-Level STEM Student Handwritten Solutions Automated Grading of Students' Handwritten Graphs: A Comparison of Meta-Learning and Vision-Large Language Models

Reference 3

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