作者位次 #4/6ACL 2026Poster· Natural Language Processing
R e FE ree: Reference-Free and Fine-Grained Method for Evaluating Factual Consistency in Real-World Code Summarization
Suyoung Bae · CheolWon Na · Jaehoon Lee · Yumin Lee · YunSeok Choi · Jee-Hyong LEE
摘要
As Large Language Models (LLMs) have become capable of generating long and descriptive code summaries, accurate and reliable evaluation of factual consistency has become a critical challenge. However, previous evaluation methods are primarily designed for short summaries of isolated code snippets...