mlsanityData to 7 Oct 2026

G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model

arXiv 2312.11370 ↗First posted 18 Dec 2023cs.CLcited by 208

On the map: Multimodal LLMs / vision-language models → Embodied and 3D vision-language models

Abstract (arXiv)

Large language models (LLMs) have shown remarkable proficiency in human-level reasoning and generation capabilities, which encourages extensive research on their application in mathematical problem solving. However, current work has been largely focused on text-based mathematical problems, with limited investigation in problems involving geometric information. Addressing this gap, we aim to enable LLMs to solve geometric problems by understanding image input. We first analyze the limitations of current Multimodal Large Language Models (MLLMs) in this area: they struggle to accurately comprehending basic geometric elements and their relationships. To overcome these challenges, we take advantage of the unique characteristics of geometric problems (such as unique geometric logical form, and geometric scalability) and the capacity of the textual LLMs to build an enriched multimodal geometry dataset based on existing data. The augmented dataset, Geo170K, contains more than 170K geometric image-caption and question-answer pairs. Utilizing our constructed Geo170K dataset, we develop G-LLaVA, which demonstrates exceptional performance in solving geometric problems, significantly outperforming GPT-4-V on the MathVista benchmark with only 7B parameters.

Key facts. Cited by 208 papers in the map (data through 7 Oct 2026). Placed in Embodied and 3D vision-language models, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 31 of its 49 references that are in the map. First posted on arXiv 18 Dec 2023.

Builds on

31 of 49 references.

References · 31

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  6. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  7. 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,304
  8. 2022Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedbackcited by 3,634
  9. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,674
  10. 2023Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyondcited by 2,179
  11. 2023MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGIcited by 2,044
  12. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,968
19 more
  1. 2023MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contextscited by 1,582
  2. 2022Least-to-Most Prompting Enables Complex Reasoning in Large Language Modelscited by 1,397
  3. 2023Shikra: Unleashing Multimodal LLM's Referential Dialogue Magiccited by 891
  4. 2023The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)cited by 677
  5. 2023WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instructcited by 618
  6. 2022Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Modelcited by 557
  7. 2023MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuningcited by 483
  8. 2021Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoningcited by 376
  9. 2022Large Language Models are Better Reasoners with Self-Verificationcited by 304
  10. 2023GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interestcited by 300
  11. 2022Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofscited by 278
  12. 2023Specializing Smaller Language Models towards Multi-Step Reasoningcited by 249
  13. 2021GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoningcited by 224
  14. 2022ZeroGen: Efficient Zero-shot Learning via Dataset Generationcited by 209
  15. 2022Generating Training Data with Language Models: Towards Zero-Shot Language Understandingcited by 199
  16. 2022UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expressioncited by 137
  17. 2022ProGen: Progressive Zero-shot Dataset Generation via In-context Feedbackcited by 67
  18. 2023Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem Provingcited by 37
  19. 2023A Symbolic Character-Aware Model for Solving Geometry Problemscited by 20

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 57; 2025: 107; 2026: 42.

208 papers.

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  1. 2024LLaVA-OneVision: Easy Visual Task Transfercited by 2,669
  2. 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,769
  3. 2024Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMscited by 822
  4. 2025Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Modelscited by 653
  5. 2024MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?cited by 573
  6. 2024We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?cited by 281
  7. 2024A Survey on Knowledge Distillation of Large Language Modelscited by 276
  8. 2024Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimizationcited by 238
  9. 2024Continual Learning of Large Language Models: A Comprehensive Surveycited by 228
  10. 2024CogVLM2: Visual Language Models for Image and Video Understandingcited by 214
  11. 2025SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Modelscited by 209
  12. 2024NVILA: Efficient Frontier Visual Language Modelscited by 206
38 more
  1. 2025MLLMs Know Where to Look: Training-free Perception of Small Visual Details with Multimodal LLMscited by 172
  2. 2024Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Searchcited by 171
  3. 2024Building and better understanding vision-language models: insights and future directionscited by 169
  4. 2024Ovis: Structural Embedding Alignment for Multimodal Large Language Modelcited by 167
  5. 2025LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMscited by 145
  6. 2024Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoderscited by 137
  7. 2025VisualPRM: An Effective Process Reward Model for Multimodal Reasoningcited by 134
  8. 2024Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Modelscited by 133
  9. 2024NVLM: Open Frontier-Class Multimodal LLMscited by 124
  10. 2024Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Modelscited by 112
  11. 2024MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Enginecited by 111
  12. 2023GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoningcited by 107
  13. 2025Baichuan-Omni-1.5 Technical Reportcited by 107
  14. 2023Mixture of Cluster-conditional LoRA Experts for Vision-language Instruction Tuningcited by 106
  15. 2024MMSearch: Benchmarking the Potential of Large Models as Multi-modal Search Enginescited by 98
  16. 2024A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discoverycited by 96
  17. 2025Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areascited by 93
  18. 2025Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning of Vision Language Modelscited by 92
  19. 2024MoVA: Adapting Mixture of Vision Experts to Multimodal Contextcited by 82
  20. 2024Holistic Autonomous Driving Understanding by Bird's-Eye-View Injected Multi-Modal Large Modelscited by 75
  21. 2025Boosting the Generalization and Reasoning of Vision Language Models with Curriculum Reinforcement Learningcited by 71
  22. 2024MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Modelscited by 69
  23. 2024Vision-Language Models Can Self-Improve Reasoning via Reflectioncited by 66
  24. 2025Unlocking Multimodal Mathematical Reasoning via Process Reward Modelcited by 64
  25. 2025VideoChat-R1.5: Visual Test-Time Scaling to Reinforce Multimodal Reasoning by Iterative Perceptioncited by 60
  26. 2024A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challengescited by 55
  27. 2025Look-Back: Implicit Visual Re-focusing in MLLM Reasoningcited by 54
  28. 2025FineVision: Open Data Is All You Needcited by 51
  29. 2025UniToken: Harmonizing Multimodal Understanding and Generation through Unified Visual Encodingcited by 49
  30. 2025STORM: Token-Efficient Long Video Understanding for Multimodal LLMscited by 46
  31. 2025FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocitiescited by 46
  32. 2025MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoningcited by 45
  33. 2025MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoningcited by 45
  34. 2025Perception-R1: Advancing Multimodal Reasoning Capabilities of MLLMs via Visual Perception Rewardcited by 45
  35. 2024MMEvol: Empowering Multimodal Large Language Models with Evol-Instructcited by 42
  36. 2025MM-IFEngine: Towards Multimodal Instruction Followingcited by 41
  37. 2025Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmarkcited by 41
  38. 2025MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verificationcited by 39

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  1. 2024Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems with Meta In-Context Learning
  2. 2024GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation
  3. 2025Do Large Language Models Truly Understand Geometric Structures?
  4. 2025Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration
  5. 2026GeoSym127K: Scalable Symbolically-verifiable Synthesis for Multimodal Geometric Reasoning
  6. 2024Beyond Lines and Circles: Unveiling the Geometric Reasoning Gap in Large Language Models
  7. 2026Measuring Representation Robustness in Large Language Models for Geometry
  8. 2026M3Kang: Evaluating Multilingual Multimodal Mathematical Reasoning in Vision-Language Models