MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems | Paper Citation Record

Observation 04501110-030e-4523-9fd0-d0f864796504 · outbound

This paper cites Large Language Models for Mathematical Reasoning: Progresses and Challenges.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Large Language Models for Mathematical Reasoning: Progresses and Challenges

Reference 1

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This paper cites Flamingo: a visual language model for few-shot learning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Flamingo: a visual language model for few-shot learning

Reference 2

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This paper cites MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms

Reference 3

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This paper cites claude-3-5-sonnet system card.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems claude-3-5-sonnet system card

Reference 4

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This paper cites OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Reference 5

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This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 6

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This paper cites GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation

Reference 7

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Observation edecfd91-e333-4d89-8e3a-823e99214da9 · outbound

This paper cites GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning

Reference 8

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Observation 958a06aa-5eac-40c1-b422-08e0704bcbb8 · outbound

This paper cites UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression

Reference 9

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Observation 1a589b01-292c-4f07-b5b9-194f7c31631b · outbound

This paper cites MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

Reference 10

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Observation 101e658f-1122-454c-a2f4-97e80169752f · outbound

This paper cites ChatCoT: Tool-Augmented Chain-of-Thought Reasoning on Chat-based Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems ChatCoT: Tool-Augmented Chain-of-Thought Reasoning on Chat-based Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.250204Z

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This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 12

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This paper cites How to learn and teach economics with large language models, including gpt.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems How to learn and teach economics with large language models, including gpt

Reference 13

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This paper cites InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model

Reference 14

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Observation e821c89d-c5c1-40c7-a44d-166aaebf846b · outbound

This paper cites Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges

Reference 15

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Observation 6b106ad4-c64b-478d-99dc-7a4f7807da6d · outbound

This paper cites More than meets the ai: Evaluating the performance of gpt-4 on computer graphics assessment questions.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems More than meets the ai: Evaluating the performance of gpt-4 on computer graphics assessment questions

Reference 16

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Observation 5beb0256-b81c-4dd1-a262-fdf3bb558d0c · outbound

This paper cites Gpt-3: Its nature, scope, limits, and consequences.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Gpt-3: Its nature, scope, limits, and consequences

Reference 17

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Observation 3b65c672-6fc4-44b1-897d-cabe73e982c0 · outbound

This paper cites Mathematical capabilities of chatgpt.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Mathematical capabilities of chatgpt

Reference 18

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This paper cites Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models

Reference 19

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Observation 253e581e-4786-46fb-aa88-3ec223495e9e · outbound

This paper cites G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model

Reference 21

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Observation 841b6d2a-3a4f-4594-a8fe-40209c44ddf4 · outbound

This paper cites LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model

Reference 22

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This paper cites SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models

Reference 23

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Observation 11f8cdf8-21c4-44ef-a526-4bca0cf0b6f6 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 24

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Observation 8be1a0c6-faaa-4be6-b6ad-8275bbed4d26 · outbound

This paper cites InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning

Reference 25

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Observation 5d4e6951-ed24-4fe8-a64a-a4946b80b801 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Measuring Mathematical Problem Solving With the MATH Dataset

Reference 26

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This paper cites Mixtral of Experts.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Mixtral of Experts

Reference 27

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This paper cites Problem representation and mathemati- cal problem solving of students of varying math ability.Jour- nal of Learning Disabilities, 47(2):103–115.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Problem representation and mathemati- cal problem solving of students of varying math ability.Jour- nal of Learning Disabilities, 47(2):103–115

Reference 28

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Observation 645b6db1-06f6-4b96-bc07-10b25774227d · outbound

This paper cites Solving quantitative reasoning problems with language mod- els.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Solving quantitative reasoning problems with language mod- els

Reference 29

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Observation 48c9f822-5b7a-424a-abc2-5f57f3713a57 · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems LLaVA-OneVision: Easy Visual Task Transfer

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.169735Z

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Observation 00cbfc93-433b-4d54-8a6d-d9dc03f3d662 · outbound

This paper cites LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 31

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Observation b02691ae-ce58-4bcf-88d0-2295120c2b83 · outbound

This paper cites Eagle: Elevating geo- metric reasoning through llm-empowered visual instruction tuning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Eagle: Elevating geo- metric reasoning through llm-empowered visual instruction tuning

Reference 32

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Observation 67859e14-02a6-4fcb-ac4f-403d97ff13b1 · outbound

This paper cites Let's Verify Step by Step.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Let's Verify Step by Step

Reference 33

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Observation 07e4644e-0b01-410d-a617-a5eafc71c9c7 · outbound

This paper cites SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models

Reference 34

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Observation 3c6e30a7-843a-41eb-9e8f-bf1a9f6237b2 · outbound

This paper cites DeepSeek-V3 Technical Report.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems DeepSeek-V3 Technical Report

Reference 35

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Observation df01849b-d623-4067-ad1b-7c9a133bf757 · outbound

This paper cites Visual instruction tuning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Visual instruction tuning

Reference 36

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Observation d02a36cf-61f9-4022-be44-d6e2618d4d31 · outbound

This paper cites MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.405426Z

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Observation 2cb1a9cd-bd36-4638-80a9-bc25a48f0ba5 · outbound

This paper cites CMM-Math: A Chinese Multimodal Math Dataset To Evaluate and Enhance the Mathematics Reasoning of Large Multimodal Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems CMM-Math: A Chinese Multimodal Math Dataset To Evaluate and Enhance the Mathematics Reasoning of Large Multimodal Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.323229Z

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Observation ea0af88a-3240-4dc3-9ac0-0d8e3af11c9b · outbound

This paper cites FineMath: A Fine-Grained Mathematical Evaluation Benchmark for Chinese Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems FineMath: A Fine-Grained Mathematical Evaluation Benchmark for Chinese Large Language Models

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.415550Z

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Observation 899ea283-a9ca-4292-a6a7-30c171db948d · outbound

This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.210289Z

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Observation 2dbfda87-5ada-43b0-b016-f330e43efcc1 · outbound

This paper cites Visaidmath: Benchmark- ing visual-aided mathematical reasoning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Visaidmath: Benchmark- ing visual-aided mathematical reasoning

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Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.443783Z

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This paper cites Language Models are Few-Shot Learners.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Language Models are Few-Shot Learners

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.317759Z

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Observation a8990542-d699-4421-b9b7-f6c1017d9d10 · outbound

This paper cites A Comprehensive Overview of Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems A Comprehensive Overview of Large Language Models

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.159208Z

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Observation e964e3ff-d2c8-4a7a-b485-52f9df544395 · outbound

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MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Unresolved cited work

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:15.013858Z

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Observation 0038f054-fb34-45fe-9d3e-9b50d6e21352 · outbound

This paper cites Introducing openai o1.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Introducing openai o1

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:05:13.440662Z

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Observation e2618233-38b4-4096-a801-39d6e6c98b85 · outbound

This paper cites GPT-4V(ision) system card.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems GPT-4V(ision) system card

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:05:13.451326Z

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Observation e0ddd60c-adc0-46a0-9bef-a7b03df183f6 · outbound

This paper cites GPT-4o system card.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems GPT-4o system card

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:05:13.432249Z

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Observation ea233217-f758-47e4-bbc8-dd1c6460ab83 · outbound

This paper cites MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.154849Z

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Observation 771a2a44-cc22-4aa9-841c-12f88370d63c · outbound

This paper cites How to solve it: A new aspect of mathematical method.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems How to solve it: A new aspect of mathematical method

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:15.008308Z

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Observation abda7305-b763-4260-b1f5-38fed4d47d6f · outbound

This paper cites We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.244265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation efc1cea2-a6e2-4542-b4c3-34958de584aa · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Learning transferable visual models from natural language supervi- sion

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.999179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 2d172e97-d16d-4b23-96e8-07f47b5f7817 · outbound

This paper cites Vision language models are blind: Failing to translate detailed visual features into words.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Vision language models are blind: Failing to translate detailed visual features into words

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.399915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation dcf95ff7-0f6f-4892-8ec6-1bf745e16e25 · outbound

This paper cites Towards robust automated math problem solving: a survey of statistical and deep learning approaches.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Towards robust automated math problem solving: a survey of statistical and deep learning approaches

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:15.002309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation c0d517e4-b3ce-43b2-9560-976539398912 · outbound

This paper cites Can llms master math? investigating large language models on math stack exchange.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Can llms master math? investigating large language models on math stack exchange

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.992576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 3484211c-d36e-4050-8f77-bc2bfc7abc99 · outbound

This paper cites P ´olya, problem solving, and education.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems P ´olya, problem solving, and education

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.995980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 4dd46c39-1c70-4bb8-91aa-3eb038061bd3 · outbound

This paper cites Survey of different large language model archi- tectures: Trends, benchmarks, and challenges.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Survey of different large language model archi- tectures: Trends, benchmarks, and challenges

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:15.005188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 10819048-7ea7-4f15-897d-3795753cc035 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 57

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.448987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 864f180e-87f7-4e60-b190-e2b7b432ba0a · outbound

This paper cites Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.279934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 72f2cf82-7060-408f-a761-ba4b8b99a23b · outbound

This paper cites Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.274854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation c0c156ee-be45-42ef-adf0-57421c45304e · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Gemini: A Family of Highly Capable Multimodal Models

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.433332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 2a55ad6a-fe36-4c88-b4a2-bb2cc3c0aafe · outbound

This paper cites Qwen2.5-llm: Extending the boundary of llms.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Qwen2.5-llm: Extending the boundary of llms

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:15.010912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 3f9ac620-acb8-4629-87de-33037e701905 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems LLaMA: Open and Efficient Foundation Language Models

Reference 62

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.304188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 131550f8-80e7-4372-89ce-17d76c15f2b2 · outbound

This paper cites Examining the potential and pitfalls of chatgpt in science and engineering problem-solving.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Examining the potential and pitfalls of chatgpt in science and engineering problem-solving

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.985873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 8d5abcb0-ffe8-4908-bcae-5337273cecc4 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.192257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation e7c99b5f-2b23-4896-81d2-441100c7da1e · outbound

This paper cites Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.410915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation a1faefd3-5a9d-4ca9-9eff-a40f8258ebac · outbound

This paper cites MathPile: A Billion-Token-Scale Pretraining Corpus for Math.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MathPile: A Billion-Token-Scale Pretraining Corpus for Math

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.299730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 7c38f806-6157-4fa4-b90f-62a288c5c96b · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large lan- guage models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Chain-of-thought prompting elicits reasoning in large lan- guage models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.989182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 1fa9af09-afa2-4139-9d61-59beb236a991 · outbound

This paper cites Chain-of-Though (CoT) prompting strategies for medical error detection and correction.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Chain-of-Though (CoT) prompting strategies for medical error detection and correction

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.370733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 9a53318a-f90d-49de-a9c0-93259932cfa7 · outbound

This paper cites LLaVA-CoT: Let Vision Language Models Reason Step-by-Step.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems LLaVA-CoT: Let Vision Language Models Reason Step-by-Step

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.186674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 5f3ec338-22a4-4ffd-bcf8-46b8987b8668 · outbound

This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.339111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation c41276d3-d9c0-47da-ab97-b5317775f06d · outbound

This paper cites MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.356075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 14049134-5bc1-40c7-bb4b-bb037c4f9f60 · outbound

This paper cites Gpt (generative pre-trained transformer)–a comprehensive review on enabling technolo- gies, potential applications, emerging challenges, and future directions.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Gpt (generative pre-trained transformer)–a comprehensive review on enabling technolo- gies, potential applications, emerging challenges, and future directions

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.982945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 0faa816b-8785-4131-8ef0-d7e34eae2c96 · outbound

This paper cites Lamm: Language-assisted multi-modal instruction-tuning dataset, framework, and benchmark.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Lamm: Language-assisted multi-modal instruction-tuning dataset, framework, and benchmark

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:15.037827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 763dcc2b-dcc3-40b5-913e-2eb20340430f · outbound

This paper cites MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.360970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation df7a226a-a6ab-489b-9d85-7137fe7d119e · outbound

This paper cites MARIO Eval: Evaluate Your Math LLM with your Math LLM--A mathematical dataset evaluation toolkit.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MARIO Eval: Evaluate Your Math LLM with your Math LLM--A mathematical dataset evaluation toolkit

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.175038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation af48fcaf-14c9-4ccc-b398-0d066deade89 · outbound

This paper cites LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.313394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 4de87810-1995-48c5-8a76-778d5fc52cc9 · outbound

This paper cites MM-LLMs: Recent Advances in MultiModal Large Language Models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MM-LLMs: Recent Advances in MultiModal Large Language Models

Reference 77

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.203706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 097a8f0a-8a30-4c14-854f-a6b279e41832 · outbound

This paper cites LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention

Reference 78

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.379700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 22234b7a-00d5-4da4-85ba-ccb440c936bc · outbound

This paper cites MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?

Reference 79

Resolution: verified exact; local_arxiv, observed 2026-05-22T22:57:13.149208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation c209adac-e703-4368-a0cb-5989f264fe0a · outbound

This paper cites MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.394341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation fb61cb14-68b1-4c57-9533-2a7d570d6265 · outbound

This paper cites Is Your Model Really A Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Is Your Model Really A Good Math Reasoner? Evaluating Mathematical Reasoning with Checklist

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.289581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation a64c61f0-973c-4b08-93b3-4248351923db · outbound

This paper cites Math-PUMA: Progressive Upward Multimodal Alignment to Enhance Mathematical Reasoning.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Math-PUMA: Progressive Upward Multimodal Alignment to Enhance Mathematical Reasoning

Reference 82

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:57:13.375512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 4d5f8327-abc2-4b51-9532-2eaaa7cae5a1 · outbound

This paper cites Solving math word problems concerning systems of equations with gpt models.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Solving math word problems concerning systems of equations with gpt models

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.976754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 6a442141-9c4f-4d95-baa6-69ceb96b16f7 · outbound

This paper cites Only Question.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Only Question

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.979532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation 12db8641-6260-48f1-ab03-5d49e3ed3877 · outbound

This paper cites an unresolved cited work.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Unresolved cited work

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:05:13.436088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation bc958bdc-cb56-4bfd-9271-e2f4e8b9a7b7 · outbound

This paper cites CoT-E” or “Acc.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems CoT-E” or “Acc

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:05:13.439796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation f04fac25-241b-4dd3-af9f-1b4c139c1d54 · outbound

This paper cites an unresolved cited work.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems Unresolved cited work

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T23:02:14.970385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

Observation f22748bb-db96-4814-8d85-24c600306bc6 · outbound

This paper cites According to the given information,△ABC is congruent to△DEB.

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems According to the given information,△ABC is congruent to△DEB

Reference 88

Resolution: malformed identifier; raw_fallback, observed 2026-05-22T23:02:14.973522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-22T06:31:00.163083+00:00.

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Reference resolution

Outbound references

Pith citing papers