34 citations · 92 across the 9 of their papers we have counts for
9 papers
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…
Pivotal Role of Language Modeling in Recommender Systems: Enriching Task-specific and Task-agnostic Representation Learning
Kyuyong Shin, Hanock Kwak, Wonjae Kim +5
Recent studies have proposed unified user modeling frameworks that leverage user behavior data from various applications. Many of them benefit from utilizing users' behavior sequen…
Scaling Law for Recommendation Models: Towards General-purpose User Representations
Kyuyong Shin, Hanock Kwak, Su Young Kim +4
Recent advancement of large-scale pretrained models such as BERT, GPT-3, CLIP, and Gopher, has shown astonishing achievements across various task domains. Unlike vision recognition…
Global-Local Item Embedding for Temporal Set Prediction
Seungjae Jung, Young-Jin Park, Jisu Jeong +4
Temporal set prediction is becoming increasingly important as many companies employ recommender systems in their online businesses, e.g., personalized purchase prediction of shoppi…
One4all User Representation for Recommender Systems in E-commerce
Kyuyong Shin, Hanock Kwak, Kyung-Min Kim +4
General-purpose representation learning through large-scale pre-training has shown promising results in the various machine learning fields. For an e-commerce domain, the objective…
A Worrying Analysis of Probabilistic Time-series Models for Sales Forecasting
Seungjae Jung, Kyung-Min Kim, Hanock Kwak +1
Probabilistic time-series models become popular in the forecasting field as they help to make optimal decisions under uncertainty. Despite the growing interest, a lack of thorough…
Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation
Kyung-Min Kim, Donghyun Kwak, Hanock Kwak +7
Graph Neural Networks (GNNs) have been emerging as a promising method for relational representation including recommender systems. However, various challenging issues of social gra…
Ways of Conditioning Generative Adversarial Networks
Hanock Kwak, Byoung-Tak Zhang
The GANs are generative models whose random samples realistically reflect natural images. It also can generate samples with specific attributes by concatenating a condition vector…
Generating Images Part by Part with Composite Generative Adversarial Networks
Hanock Kwak, Byoung-Tak Zhang
Image generation remains a fundamental problem in artificial intelligence in general and deep learning in specific. The generative adversarial network (GAN) was successful in gener…