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Yongji Wang

2 accepted papers

2024

CodeM: Less Data Yields More Versatility via Ability Matrix

ACL 2024findings

In the era of code large language models (code LLMs), data engineering plays a pivotal role during the instruction fine-tuning phase. To train a versatile model, previous efforts devote tremendous efforts into crafting instruction data covering all the downstream scenarios. Nonetheless, this will in…

2022

CERT: Continual Pre-training on Sketches for Library-oriented Code Generation

IJCAI 2022poster

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, thanks to the success of pre-training techniques, large language models are tr…