13 citations · 14 across the 12 of their papers we have counts for
5 papers · 1 filter
Reward-based Input Construction for Cross-document Relation Extraction
Byeonghu Na, Suhyeon Jo, Yeongmin Kim +1
Relation extraction (RE) is a fundamental task in natural language processing, aiming to identify relations between target entities in text. While many RE methods are designed for…
Diffusion Rejection Sampling
Byeonghu Na, Yeongmin Kim, Minsang Park +3
Recent advances in powerful pre-trained diffusion models encourage the development of methods to improve the sampling performance under well-trained diffusion models. This paper in…
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim, Kwanghyeon Lee, Minsang Park +2
Diffusion-based representation learning has achieved substantial attention due to its promising capabilities in latent representation and sample generation. Recent studies have emp…
Training Unbiased Diffusion Models From Biased Dataset
Yeongmin Kim, Byeonghu Na, Minsang Park +4
With significant advancements in diffusion models, addressing the potential risks of dataset bias becomes increasingly important. Since generated outputs directly suffer from datas…
Label-Noise Robust Diffusion Models
Byeonghu Na, Yeongmin Kim, HeeSun Bae +4
Conditional diffusion models have shown remarkable performance in various generative tasks, but training them requires large-scale datasets that often contain noise in conditional…