Austin Parkinrecsys-summarize[WSDM’23]Towards Universal Cross-Domain Recommendation — reviewBackgroundMay 18May 18
Austin Parkinrecsys-summarize[WSDM’24]Long-Term Value of Exploration: Measurements, Findings and Algorithms (Best Paper) —…Today, I will review the paper “Long-Term Value of Exploration: Measurements, Findings, and Algorithms”, which was presented by Google and…Apr 21Apr 21
Austin Parkinrecsys-summarize[WSDM’24]Long-Term Value of Exploration: Measurements, Findings and Algorithms (Best Paper) — 리뷰오늘은 Google과 Google Deepmind에서 발표하고 WSDM2024에서 best paper로 선정된 Long-Term Value of Exploration: Measurements, Findings and Algorithms 을 개인적인…Apr 21Apr 21
Austin Parkinrecsys-summarizeTrending Now: Modeling Trend Recommendations — reviewDefine the concept of “trend” in recommendation scenarios and propose a model to discover trending items.Mar 41Mar 41
Austin Parkinrecsys-summarize[RecSys’23]Trending Now: Modeling Trend Recommendations 리뷰추천 상황에서 trend의 정의를 내리고 trending item을 찾는 모델 제안Mar 3Mar 3
Austin Parkinrecsys-summarize[TOIS’23]Personalized Prompt Learning for Explainable Recommendation — reviewExplainable Recommender System using LLMFeb 19Feb 19
Austin Parkinrecsys-summarize[TOIS’23]Personalized Prompt Learning for Explainable Recommendation 리뷰LLM을 활용한 설명가능한 추천 시스템Feb 18Feb 18
Austin Parkinrecsys-summarize[CIKM’23]Integrating Summarization and Retrieval for Enhanced Personalization via Large Language…This paper introduces techniques to enhance the personalized task performance ability of the LLMFeb 4Feb 4
Austin Parkinrecsys-summarize[CIKM’23]Integrating Summarization and Retrieval for Enhanced Personalization via Large Language…LLM의 개인화 task 수행 능력을 향상시키는 테크닉을 소개하는 논문입니다.Feb 4Feb 4