5 papers
MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender
Tongyoung Kim, Soojin Yoon, SeongKu Kang +2
Language Models (LMs) have been widely used in recommender systems to incorporate textual information of items into item IDs, leveraging their advanced language understanding and g…
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…
Stop Playing the Guessing Game! Target-free User Simulation for Evaluating Conversational Recommender Systems
Sunghwan Kim, Kwangwook Seo, Tongyoung Kim +2
Recent approaches in Conversational Recommender Systems (CRSs) have tried to simulate real-world users engaging in conversations with CRSs to create more realistic testing environm…
Towards Personalized Conversational Sales Agents: Contextual User Profiling for Strategic Action
Tongyoung Kim, Jeongeun Lee, Soojin Yoon +2
Conversational Recommender Systems (CRSs)aim to engage users in dialogue to provide tailored recommendations. While traditional CRSs focus on eliciting preferences and retrieving i…
Unsupervised Robust Cross-Lingual Entity Alignment via Neighbor Triple Matching with Entity and Relation Texts
Soojin Yoon, Sungho Ko, Tongyoung Kim +3
Cross-lingual entity alignment (EA) enables the integration of multiple knowledge graphs (KGs) across different languages, providing users with seamless access to diverse and compr…