mlsanityData to 7 Oct 2026

LLMs for Coding and Robotics Education

arXiv 2402.06116 ↗First posted 9 Feb 2024cs.RO cs.AIcited by 9

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

Abstract (arXiv)

Large language models and multimodal large language models have revolutionized artificial intelligence recently. An increasing number of regions are now embracing these advanced technologies. Within this context, robot coding education is garnering increasing attention. To teach young children how to code and compete in robot challenges, large language models are being utilized for robot code explanation, generation, and modification. In this paper, we highlight an important trend in robot coding education. We test several mainstream large language models on both traditional coding tasks and the more challenging task of robot code generation, which includes block diagrams. Our results show that GPT-4V outperforms other models in all of our tests but struggles with generating block diagram images.

Key facts. Cited by 9 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 19 of its 44 references that are in the map. First posted on arXiv 9 Feb 2024.

Builds on

19 of 44 references.

Closest ancestors · 1

Same direction, newest first

  1. 2024Large Language Models for Robotics: Opportunities, Challenges, and Perspectives9 Jan

Other references · 18

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2023GPT-4 Technical Reportcited by 18,132
  5. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  6. 2021Evaluating Large Language Models Trained on Codecited by 8,053
  7. 2023Visual Instruction Tuningcited by 7,792
  8. 2020CodeBERT: A Pre-Trained Model for Programming and Natural Languagescited by 1,286
  9. 2021CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generationcited by 732
  10. 2022Visual Programming: Compositional visual reasoning without trainingcited by 507
  11. 2023ChatGPT for Robotics: Design Principles and Model Abilitiescited by 296
  12. 2018code2seq: Generating Sequences from Structured Representations of Codecited by 177
6 more
  1. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Modelscited by 152
  2. 2023When Brain-inspired AI Meets AGIcited by 54
  3. 2023CodeLMSec Benchmark: Systematically Evaluating and Finding Security Vulnerabilities in Black-Box Code Language Modelscited by 52
  4. 2023AI-assisted coding: Experiments with GPT-4cited by 43
  5. 2023RobotGPT: Robot Manipulation Learning from ChatGPTcited by 39
  6. 2023Outline, Then Details: Syntactically Guided Coarse-To-Fine Code Generationcited by 27

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 0; 2026: 1.

9 papers.

  1. 2024Large Language Models for Manufacturingcited by 24
  2. 2024Transcending Language Boundaries: Harnessing LLMs for Low-Resource Language Translationcited by 12
  3. 2024Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reportscited by 6
  4. 2024LLeMpower: Understanding Disparities in the Control and Access of Large Language Modelscited by 5
  5. 2024Foundation Models for Low-Resource Language Education (Vision Paper)cited by 5
  6. 2024Examining the Commitments and Difficulties Inherent in Multimodal Foundation Models for Street View Imagerycited by 4
  7. 2024Legal Evalutions and Challenges of Large Language Modelscited by 4
  8. 2024Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projectioncited by 2
  9. 2026Domain-Adaptable Reinforcement Learning for Code Generation with Dense Rewardscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023More Robots are Coming: Large Multimodal Models (ChatGPT) can Solve Visually Diverse Images of Parsons Problems
  2. 2025Code-Vision: Evaluating Multimodal LLMs Logic Understanding and Code Generation Capabilities
  3. 2024MMCode: Benchmarking Multimodal Large Language Models for Code Generation with Visually Rich Programming Problems
  4. 2024Prompt Selection and Augmentation for Few Examples Code Generation in Large Language Model and its Application in Robotics Control
  5. 2026Training and Benchmarking Code Generation for Physics-Inspired Animations
  6. 2023GPT4Tools: Teaching Large Language Model to Use Tools via Self-instruction
  7. 2026A Pragmatic VLA Foundation Model
  8. 2023Demo2Code: From Summarizing Demonstrations to Synthesizing Code via Extended Chain-of-Thought