mlsanityData to 14 Oct 2026

Code Generation and Algorithmic Problem Solving Using Llama 3.1 405B

arXiv 2409.19027 ↗First posted 26 Sep 2024cs.CL cs.SEcited by 7

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Abstract (arXiv)

Code generation by Llama 3.1 models, such as Meta's Llama 3.1 405B, represents a significant advancement in the field of artificial intelligence, particularly in natural language processing and programming automation. This paper explores the capabilities and applications of Llama-driven code generation, highlighting its ability to translate natural language prompts into executable code across multiple programming languages. Key features include contextual awareness, multi-language support, and enhanced debugging and optimization functionalities. By examining these aspects, we illustrate how Llama can serve as a versatile tool for developers of all skill levels, improving productivity and efficiency in software development. The potential implications for education, industry, and the future of coding practices are also discussed, underscoring the transformative impact of AI in programming. Experimentation shows that while Llama 3.1 405B performs well with simple algorithmic and data structure based problems, it still struggles with problems on Quantum Computing, Bioinformatics, and Artificial Intelligence.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 23 of its 34 references that are in the map. First posted on arXiv 26 Sep 2024.

Builds on

23 of 34 references.

References · 23

  1. 2017Attention Is All You Needcited by 60,361
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2024The Llama 3 Herd of Modelscited by 14,715
  4. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  5. 2021Program Synthesis with Large Language Modelscited by 3,637
  6. 2022Competition-Level Code Generation with AlphaCodecited by 1,462
  7. 2023BooookScore: A systematic exploration of book-length summarization in the era of LLMscited by 137
  8. 2022Few-shot training LLMs for project-specific code-summarizationcited by 129
  9. 2023How Ready are Pre-trained Abstractive Models and LLMs for Legal Case Judgement Summarization?cited by 43
  10. 2024Applicability of Large Language Models and Generative Models for Legal Case Judgement Summarizationcited by 23
  11. 2024A Novel Multi-Stage Prompting Approach for Language Agnostic MCQ Generation using GPTcited by 19
  12. 2024From Text to Transformation: A Comprehensive Review of Large Language Models' Versatilitycited by 19
11 more
  1. 2024Exploring the Capabilities of Prompted Large Language Models in Educational and Assessment Applicationscited by 12
  2. 2024How Ready Are Generative Pre-trained Large Language Models for Explaining Bengali Grammatical Errors?cited by 11
  3. 2023Fact-based Court Judgment Predictioncited by 10
  4. 2023Nonet at SemEval-2023 Task 6: Methodologies for Legal Evaluationcited by 9
  5. 2023Harnessing the Power of Prompt-based Techniques for Generating School-Level Questions using Large Language Modelscited by 9
  6. 2024Enhancing Computer Programming Education with LLMs: A Study on Effective Prompt Engineering for Python Code Generationcited by 9
  7. 2024How Effective is GPT-4 Turbo in Generating School-Level Questions from Textbooks Based on Bloom's Revised Taxonomy?cited by 8
  8. 2023Questioning Biases in Case Judgment Summaries: Legal Datasets or Large Language Models?cited by 7
  9. 2024Artificial Intelligence (AI) in Legal Data Miningcited by 6
  10. 2023Prompted Zero-Shot Multi-label Classification of Factual Incorrectness in Machine-Generated Summariescited by 5
  11. 2024AICoderEval: Improving AI Domain Code Generation of Large Language Modelscited by 2

Built on by

Cited by year

Citing papers per year: 2024: 3; 2025: 4.

7 papers.

  1. 2025LLM-ProS: Analyzing Large Language Models' Performance in Competitive Problem Solvingcited by 6
  2. 2025Smaller = Weaker? Benchmarking Robustness of Quantized LLMs in Code Generationcited by 3
  3. 2024Prompt Engineering Using GPT for Word-Level Code-Mixed Language Identification in Low-Resource Dravidian Languagescited by 2
  4. 2025Knowledge Graph-Guided Multi-Agent Distillation for Reliable Industrial Question Answering with Datasetscited by 1
  5. 2024Cancer-Answer: Empowering Cancer Care with Advanced Large Language Modelscited by 0
  6. 2024CryptoLLM: Unleashing the Power of Prompted LLMs for SmartQnA and Classification of Crypto Postscited by 0
  7. 2025KunlunBaize: LLM with Multi-Scale Convolution and Multi-Token Prediction Under TransformerX Frameworkcited by 0