15 citations · 15 across the 5 of their papers we have counts for
5 papers
Inference-Free Multimodal Learned Sparse Retrieval for Production-Scale Visual Document Search
Gyu-Hwung Cho, Youngjune Lee, Kiyoon Jeong +5
As large-scale visual-document corpora such as arXiv papers and enterprise PDFs continue to grow, visual-document retrieval has gained increasing attention; yet it still lacks a de…
Sparse and Dense Retrievers Learn Better Together: Joint Sparse-Dense Optimization for Text-Image Retrieval
Jonghyun Song, Youngjune Lee, Gyu-Hwung Cho +3
Vision-Language Pretrained (VLP) models have achieved impressive performance on multimodal tasks, including text-image retrieval, based on dense representations. Meanwhile, Learned…
IRA: Adaptive Interest-aware Representation and Alignment for Personalized Multi-interest Retrieval
Youngjune Lee, Haeyu Jeong, Changgeon Lim +5
Online community platforms require dynamic personalized retrieval and recommendation that can continuously adapt to evolving user interests and new documents. However, optimizing m…
RRADistill: Distilling LLMs' Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine
Nayoung Choi, Youngjune Lee, Gyu-Hwung Cho +10
Large Language Models (LLMs) excel at understanding the semantic relationships between queries and documents, even with lengthy and complex long-tail queries. These queries are cha…
MvFS: Multi-view Feature Selection for Recommender System
Youngjune Lee, Yeongjong Jeong, Keunchan Park +1
Feature selection, which is a technique to select key features in recommender systems, has received increasing research attention. Recently, Adaptive Feature Selection (AdaFS) has…