5 papers
IPQA: A Benchmark for Core Intent Identification in Personalized Question Answering
Jieyong Kim, Maryam Amirizaniani, Soojin Yoon +1
Intent identification serves as the foundation for generating appropriate responses in personalized question answering (PQA). However, existing benchmarks evaluate only response qu…
RPM: Reasoning-Level Personalization for Black-Box Large Language Models
Jieyong Kim, Tongyoung Kim, Soojin Yoon +2
While black-box large language models are widely deployed, they produce generic outputs that overlook individual user preferences. Current personalization methods are fundamentally…
Review-driven Personalized Preference Reasoning with Large Language Models for Recommendation
Jieyong Kim, Hyunseo Kim, Hyunjin Cho +4
Recent advancements in Large Language Models (LLMs) have demonstrated exceptional performance across a wide range of tasks, generating significant interest in their application to…
Make Compound Sentences Simple to Analyze: Learning to Split Sentences for Aspect-based Sentiment Analysis
Yongsik Seo, Sungwon Song, Ryang Heo +2
In the domain of Aspect-Based Sentiment Analysis (ABSA), generative methods have shown promising results and achieved substantial advancements. However, despite these advancements,…
Self-Consistent Reasoning-based Aspect-Sentiment Quad Prediction with Extract-Then-Assign Strategy
Jieyong Kim, Ryang Heo, Yongsik Seo +3
In the task of aspect sentiment quad prediction (ASQP), generative methods for predicting sentiment quads have shown promising results. However, they still suffer from imprecise pr…