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On the Effectiveness of Large Language Models in Domain-Specific Code Generation

https://doi.org/10.1145/3697012
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot
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Know-How in Programming Tasks: From Textual Tutorials to Task-Oriented Knowledge Graph
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No Need to Lift a Finger Anymore? Assessing the Quality of Code Generation by ChatGPT
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G otta : Generative Few-shot Question Answering by Prompt-based Cloze Data Augmentation
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A systematic evaluation of large language models of code
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Few-shot training LLMs for project-specific code-summarization
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CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X
inferredcites →https://doi.org/10.1145/3597503.3608137openalex-snapshot
Prompting Is All You Need: Automated Android Bug Replay with Large Language Models
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Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study
inferredcites →https://doi.org/10.1145/3638247openalex-snapshot
Prompt Sapper: A LLM-Empowered Production Tool for Building AI Chains
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Can ChatGPT Support Developers? An Empirical Evaluation of Large Language Models for Code Generation
inferredcites →https://doi.org/10.1145/3652156openalex-snapshot
Do Code Summarization Models Process Too Much Information? Function Signature May Be All That Is Needed
inferredcites →https://doi.org/10.1145/3661167.3661216openalex-snapshot
Using Large Language Models to Generate JUnit Tests: An Empirical Study
inferredcites →https://doi.org/10.1145/3794763openalex-snapshot
Proceedings of the 2026 34th IEEE/ACM International Conference on Program Comprehension
inferredcites →https://doi.org/10.18653/v1/2021.acl-long.353openalex-snapshot
Prefix-Tuning: Optimizing Continuous Prompts for Generation
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.243openalex-snapshot
The Power of Scale for Parameter-Efficient Prompt Tuning
inferredcites →https://doi.org/10.18653/v1/2022.bigscience-1.9openalex-snapshot
GPT-NeoX-20B: An Open-Source Autoregressive Language Model
inferredcites →https://doi.org/10.18653/v1/2022.findings-emnlp.21openalex-snapshot
When Language Model Meets Private Library
inferredcites →https://doi.org/10.18653/v1/2023.emnlp-main.757openalex-snapshot
Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models
inferredcites →https://doi.org/10.18653/v1/2023.findings-acl.325openalex-snapshot
CodePrompt: Task-Agnostic Prefix Tuning for Program and Language Generation
inferredcites →https://doi.org/10.24963/ijcai.2022/329openalex-snapshot
CERT: Continual Pre-training on Sketches for Library-oriented Code Generation
inferredcites →https://doi.org/10.5281/zenodo.5297715openalex-snapshot
GPT-Neo: Large Scale Autoregressive Language Modeling with Mesh-Tensorflow

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