no code implementations • Findings (NAACL) 2022 • Haeju Lee, Oh Joon Kwon, Yunseon Choi, Minho Park, Ran Han, Yoonhyung Kim, Jinhyeon Kim, Youngjune Lee, Haebin Shin, Kangwook Lee, Kee-Eung Kim
The Situated Interactive Multi-Modal Conversations (SIMMC) 2. 0 aims to create virtual shopping assistants that can accept complex multi-modal inputs, i. e. visual appearances of objects and user utterances.
Ranked #2 on
Response Generation
on SIMMC2.0
no code implementations • 8 Oct 2024 • Nayoung Choi, Youngjune Lee, Gyu-Hwung Cho, Haeyu Jeong, Jungmin Kong, Saehun Kim, Keunchan Park, Sarah Cho, Inchang Jeong, Gyohee Nam, Sunghoon Han, Wonil Yang, Jaeho Choi
Large Language Models (LLMs) excel at understanding the semantic relationships between queries and documents, even with lengthy and complex long-tail queries.
1 code implementation • 5 Sep 2023 • Youngjune Lee, Yeongjong Jeong, Keunchan Park, SeongKu Kang
Feature selection, which is a technique to select key features in recommender systems, has received increasing research attention.
no code implementations • 7 Dec 2021 • Youngjune Lee, Oh Joon Kwon, Haeju Lee, Joonyoung Kim, Kangwook Lee, Kee-Eung Kim
For this reason, data-centric approaches are crucial for the automation of machine learning operation pipeline.
1 code implementation • 8 Sep 2021 • Youngjune Lee, Kee-Eung Kim
Knowledge Distillation (KD), which transfers the knowledge of a well-trained large model (teacher) to a small model (student), has become an important area of research for practical deployment of recommender systems.