23 citations · 45 across the 7 of their papers we have counts for
9 papers
Topic Taxonomy Expansion via Hierarchy-Aware Topic Phrase Generation
Dongha Lee, Jiaming Shen, Seonghyeon Lee +3
Topic taxonomies display hierarchical topic structures of a text corpus and provide topical knowledge to enhance various NLP applications. To dynamically incorporate new topic info…
Consensus Learning from Heterogeneous Objectives for One-Class Collaborative Filtering
SeongKu Kang, Dongha Lee, Wonbin Kweon +2
Over the past decades, for One-Class Collaborative Filtering (OCCF), many learning objectives have been researched based on a variety of underlying probabilistic models. From our a…
Toward Interpretable Semantic Textual Similarity via Optimal Transport-based Contrastive Sentence Learning
Seonghyeon Lee, Dongha Lee, Seongbo Jang +1
Recently, finetuning a pretrained language model to capture the similarity between sentence embeddings has shown the state-of-the-art performance on the semantic textual similarity…
TaxoCom: Topic Taxonomy Completion with Hierarchical Discovery of Novel Topic Clusters
Dongha Lee, Jiaming Shen, SeongKu Kang +3
Topic taxonomies, which represent the latent topic (or category) structure of document collections, provide valuable knowledge of contents in many applications such as web search a…
Weakly Supervised Temporal Anomaly Segmentation with Dynamic Time Warping
Dongha Lee, Sehun Yu, Hyunjun Ju +1
Most recent studies on detecting and localizing temporal anomalies have mainly employed deep neural networks to learn the normal patterns of temporal data in an unsupervised manner…
Out-of-Manifold Regularization in Contextual Embedding Space for Text Classification
Seonghyeon Lee, Dongha Lee, Hwanjo Yu
Recent studies on neural networks with pre-trained weights (i.e., BERT) have mainly focused on a low-dimensional subspace, where the embedding vectors computed from input words (or…