Papers Library-Oriented Code Generation
“Library-Oriented Code Generation” 태그가 달린 논문 5편 · 필터 해제
ObscuraCoder: Powering Efficient Code LM Pre-Training Via Obfuscation Grounding
Language models (LMs) have become a staple of the code-writing toolbox. Their pre-training recipe has, however, remained stagnant over recent years, barring the occasional changes in data sourcing and filtering strategie…
Code CompletionCode GenerationLibrary-Oriented Code GenerationAutoCoder: Enhancing Code Large Language Model with \textsc{AIEV-Instruct}
We introduce AutoCoder, the first Large Language Model to surpass GPT-4 Turbo (April 2024) and GPT-4o in pass@1 on the Human Eval benchmark test ($\mathbf{90.9\%}$ vs. $\mathbf{90.2\%}$). In addition, AutoCoder offers a …
Class-level Code GenerationCode CompletionCode GenerationCode Repair+8Compositional API Recommendation for Library-Oriented Code Generation
Large language models (LLMs) have achieved exceptional performance in code generation. However, the performance remains unsatisfactory in generating library-oriented code, especially for the libraries not present in the …
Code GenerationLibrary-Oriented Code GenerationCodeGen4Libs: A Two-Stage Approach for Library-Oriented Code Generation
Automated code generation has been extensively studied in recent literature. In this work, we first survey 66 participants to motivate a more pragmatic code generation scenario, i.e., library-oriented code generation, wh…
Code GenerationLibrary-Oriented Code GenerationCERT: Continual Pre-Training on Sketches for Library-Oriented Code Generation
Code generation is a longstanding challenge, aiming to generate a code snippet based on a natural language description. Usually, expensive text-code paired data is essential for training a code generation model. Recently…
Code GenerationLibrary-Oriented Code Generation