15 citations · 30 across the 7 of their papers we have counts for
8 papers
Unveiling Key Aspects of Fine-Tuning in Sentence Embeddings: A Representation Rank Analysis
Euna Jung, Jaeill Kim, Jungmin Ko +2
The latest advancements in unsupervised learning of sentence embeddings predominantly involve employing contrastive learning-based (CL-based) fine-tuning over pre-trained language…
On-Off Pattern Encoding and Path-Count Encoding as Deep Neural Network Representations
Euna Jung, Jaekeol Choi, EungGu Yun +1
Understanding the encoded representation of Deep Neural Networks (DNNs) has been a fundamental yet challenging objective. In this work, we focus on two possible directions for anal…
Evaluating Feature Attribution Methods for Electrocardiogram
Jangwon Suh, Jimyeong Kim, Euna Jung +1
The performance of cardiac arrhythmia detection with electrocardiograms(ECGs) has been considerably improved since the introduction of deep learning models. In practice, the high p…
Isotropic Representation Can Improve Dense Retrieval
Euna Jung, Jungwon Park, Jaekeol Choi +2
The recent advancement in language representation modeling has broadly affected the design of dense retrieval models. In particular, many of the high-performing dense retrieval mod…
Finding Inverse Document Frequency Information in BERT
Jaekeol Choi, Euna Jung, Sungjun Lim +1
For many decades, BM25 and its variants have been the dominant document retrieval approach, where their two underlying features are Term Frequency (TF) and Inverse Document Frequen…
Semi-Siamese Bi-encoder Neural Ranking Model Using Lightweight Fine-Tuning
Euna Jung, Jaekeol Choi, Wonjong Rhee
A BERT-based Neural Ranking Model (NRM) can be either a crossencoder or a bi-encoder. Between the two, bi-encoder is highly efficient because all the documents can be pre-processed…
Improving Bi-encoder Document Ranking Models with Two Rankers and Multi-teacher Distillation
Jaekeol Choi, Euna Jung, Jangwon Suh +1
BERT-based Neural Ranking Models (NRMs) can be classified according to how the query and document are encoded through BERT's self-attention layers - bi-encoder versus cross-encoder…
Short-term Traffic Prediction with Deep Neural Networks: A Survey
Kyungeun Lee, Moonjung Eo, Euna Jung +2
In modern transportation systems, an enormous amount of traffic data is generated every day. This has led to rapid progress in short-term traffic prediction (STTP), in which deep l…