Jee-Hyong LEE

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...

Recently, Large Language Models (LLM) have emerged as a promising paradigm for sequential recommendation. In sequential recommendation, effectively integrating diverse user preferences is essential for improving LLM performance, as users often exhibit multiple interests across different contexts....

Text-to-SQL enables users to query databases using natural language by generating executable SQL queries. Recent methods have increasingly adopted Large Language Models based reinforcement learning (RL) to leverage execution feedback for training. However, existing RL methods assign uniform query...