3 citations · 5 across the 11 of their papers we have counts for
6 papers · 1 filter
Towards Reliable AI Model Deployments: Multiple Input Mixup for Out-of-Distribution Detection
Dasol Choi, Dongbin Na
Recent remarkable success in the deep-learning industries has unprecedentedly increased the need for reliable model deployment. For example, the model should alert the user if the…
Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems
Dasol Choi, Dongbin Na
Machine unlearning is a crucial tool for enabling a classification model to forget specific data that are used in the training time. Recently, various studies have presented machin…
KoMultiText: Large-Scale Korean Text Dataset for Classifying Biased Speech in Real-World Online Services
Dasol Choi, Jooyoung Song, Eunsun Lee +3
With the growth of online services, the need for advanced text classification algorithms, such as sentiment analysis and biased text detection, has become increasingly evident. The…
A New Korean Text Classification Benchmark for Recognizing the Political Intents in Online Newspapers
Beomjune Kim, Eunsun Lee, Dongbin Na
Many users reading online articles in various magazines may suffer considerable difficulty in distinguishing the implicit intents in texts. In this work, we focus on automatically…
New Benchmarks for Asian Facial Recognition Tasks: Face Classification with Large Foundation Models
Jinwoo Seo, Soora Choi, Eungyeom Ha +2
The face classification system is an important tool for recognizing personal identity properly. This paper introduces a new Large-Scale Korean Influencer Dataset named KoIn. Our pr…
HOD: A Benchmark Dataset for Harmful Object Detection
Eungyeom Ha, Heemook Kim, Sung Chul Hong +1
Recent multi-media data such as images and videos have been rapidly spread out on various online services such as social network services (SNS). With the explosive growth of online…