135 citations · 272 across the 24 of their papers we have counts for
7 papers · 1 filter
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong +2
Denoising diffusion probabilistic models (DDPM) have shown remarkable performance in unconditional image generation. However, due to the stochasticity of the generative process in…
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection
Yonghyun Jeong, Doyeon Kim, Seungjai Min +3
The advancement in numerous generative models has a two-fold effect: a simple and easy generation of realistic synthesized images, but also an increased risk of malicious abuse of…
Matrix Encoding Networks for Neural Combinatorial Optimization
Yeong-Dae Kwon, Jinho Choo, Iljoo Yoon +3
Machine Learning (ML) can help solve combinatorial optimization (CO) problems better. A popular approach is to use a neural net to compute on the parameters of a given CO problem a…
KoreALBERT: Pretraining a Lite BERT Model for Korean Language Understanding
Hyunjae Lee, Jaewoong Yoon, Bonggyu Hwang +3
A Lite BERT (ALBERT) has been introduced to scale up deep bidirectional representation learning for natural languages. Due to the lack of pretrained ALBERT models for Korean langua…
Analyzing Zero-shot Cross-lingual Transfer in Supervised NLP Tasks
Hyunjin Choi, Judong Kim, Seongho Joe +2
In zero-shot cross-lingual transfer, a supervised NLP task trained on a corpus in one language is directly applicable to another language without any additional training. A source…
Evaluation of BERT and ALBERT Sentence Embedding Performance on Downstream NLP Tasks
Hyunjin Choi, Judong Kim, Seongho Joe +1
Contextualized representations from a pre-trained language model are central to achieve a high performance on downstream NLP task. The pre-trained BERT and A Lite BERT (ALBERT) mod…
SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning
Byoungjip Kim, Jinho Choo, Yeong-Dae Kwon +3
This paper introduces SelfMatch, a semi-supervised learning method that combines the power of contrastive self-supervised learning and consistency regularization. SelfMatch consist…