1 citations · 4 across the 13 of their papers we have counts for
4 papers · 1 filter
TokDrift: When LLM Speaks in Subwords but Code Speaks in Grammar
Yinxi Li, Yuntian Deng, Pengyu Nie
Large language models (LLMs) for code rely on subword tokenizers, such as byte-pair encoding (BPE), learned from mixed natural language text and programming language code but drive…
NL in the Middle: Code Translation with LLMs and Intermediate Representations
Chi-en Amy Tai, Pengyu Nie, Lukasz Golab +1
Studies show that large language models (LLMs) produce buggy code translations. One promising avenue to improve translation accuracy is through intermediate representations, which…
Mix-of-Language-Experts Architecture for Multilingual Programming
Yifan Zong, Yuntian Deng, Pengyu Nie
Large language models (LLMs) have demonstrated impressive capabilities in aiding developers with tasks like code comprehension, generation, and translation. Supporting multilingual…
Suggesting Code Edits in Interactive Machine Learning Notebooks Using Large Language Models
Bihui Jin, Jiayue Wang, Pengyu Nie
Machine learning developers frequently use interactive computational notebooks, such as Jupyter notebooks, to host code for data processing and model training. Jupyter notebooks pr…