10 papers
WatchLens: A Configurable Platform for Online Video Recommendation Experiments
Deogyong Kim, Dongha Lee
Studying how video recommender systems shape user behavior requires online experiments that link playback behavior with the recommendation conditions that produced it. Existing use…
Personalizing Embodied Multimodal Large Language Model Agents over Long-term User Interactions
Jeongeun Lee, Chanyoung Park, Dongha Lee
Multimodal large language model (MLLM)-based embodied agents have shown strong potential for solving complex tasks in physical environments. However, personalized assistance requir…
Will It Go Viral? Grounding Micro-Video Popularity Prediction on the Open Web
Ryang Heo, Dongha Lee
Micro-video popularity prediction (MVPP) forecasts the popularity a newly uploaded short-form video will attract within a fixed number of days after upload. This task supports down…
PAIR: Prefix-Aware Internal Reward Model for Multi-Turn Agent Optimization
Wonjoong Kim, Yeonjun In, Sangwu Park +2
A significant hurdle for current LLMs is the execution of complex, multi-stage tasks. Group Relative Policy Optimization (GRPO) has been emerging as a leading choice, but its relia…
Offline Reasoning for Efficient Recommendation: LLM-Empowered Persona-Profiled Item Indexing
Deogyong Kim, Junseong Lee, Jeongeun Lee +4
Recent advances in large language models (LLMs) offer new opportunities for recommender systems by capturing the nuanced semantics of user interests and item characteristics throug…
Personalized Reward Modeling for Text-to-Image Generation
Jeongeun Lee, Ryang Heo, Dongha Lee
Recent text-to-image (T2I) models generate semantically coherent images from textual prompts, yet evaluating how well they align with individual user preferences remains an open ch…