output
20162026
most citedBioBERT: a pre-trained biomedical language representation model for biomedical text mining

7.5k citations

Showing 2022Show all

12 papers · 1 filter

cs.CL2022★ 6 cited

Evaluating the Knowledge Dependency of Questions

Hyeongdon Moon, Yoonseok Yang, Jamin Shin +6

The automatic generation of Multiple Choice Questions (MCQ) has the potential to reduce the time educators spend on student assessment significantly. However, existing evaluation m…

cs.LG2022★ 10 cited

Residual Correction in Real-Time Traffic Forecasting

Daejin Kim, Youngin Cho, Dongmin Kim +2

Predicting traffic conditions is tremendously challenging since every road is highly dependent on each other, both spatially and temporally. Recently, to capture this spatial and t…

cs.IR2022★ 14 cited

SpaDE: Improving Sparse Representations using a Dual Document Encoder for First-stage Retrieval

Eunseong Choi, Sunkyung Lee, Minjin Choi +3

Sparse document representations have been widely used to retrieve relevant documents via exact lexical matching. Owing to the pre-computed inverted index, it supports fast ad-hoc s…

cs.LG2022★ 14 cited

e-CLIP: Large-Scale Vision-Language Representation Learning in E-commerce

Wonyoung Shin, Jonghun Park, Taekang Woo +3

Understanding vision and language representations of product content is vital for search and recommendation applications in e-commerce. As a backbone for online shopping platforms…

cs.LG2022★ 26 cited

GenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learning

Kyunghoon Hur, Jungwoo Oh, Junu Kim +7

Despite the remarkable progress in the development of predictive models for healthcare, applying these algorithms on a large scale has been challenging. Algorithms trained on a par…

cs.CV2022★ 38 cited

Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmark

Martin Humenberger, Yohann Cabon, Noé Pion +5

Visual localization, i.e., camera pose estimation in a known scene, is a core component of technologies such as autonomous driving and augmented reality. State-of-the-art localizat…

cs.CV2022★ 13 cited

ReFine: Re-randomization before Fine-tuning for Cross-domain Few-shot Learning

Jaehoon Oh, Sungnyun Kim, Namgyu Ho +3

Cross-domain few-shot learning (CD-FSL), where there are few target samples under extreme differences between source and target domains, has recently attracted huge attention. Rece…

cs.LG2022★ 20 cited

FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning

SangMook Kim, Wonyoung Shin, Soohyuk Jang +2

Robustness is becoming another important challenge of federated learning in that the data collection process in each client is naturally accompanied by noisy labels. However, it is…

cs.LG2022★ 21 cited

Uniform Manifold Approximation with Two-phase Optimization

Hyeon Jeon, Hyung-Kwon Ko, Soohyun Lee +2

We introduce Uniform Manifold Approximation with Two-phase Optimization (UMATO), a dimensionality reduction (DR) technique that improves UMAP to capture the global structure of hig…

cs.LG2022★ 7 cited

Metropolis-Hastings Data Augmentation for Graph Neural Networks

Hyeonjin Park, Seunghun Lee, Sihyeon Kim +5

Graph Neural Networks (GNNs) often suffer from weak-generalization due to sparsely labeled data despite their promising results on various graph-based tasks. Data augmentation is a…

eess.AS2022★ 4 cited

Automatic speaker verification spoofing and deepfake detection using wav2vec 2.0 and data augmentation

Hemlata Tak, Massimiliano Todisco, Xin Wang +3

The performance of spoofing countermeasure systems depends fundamentally upon the use of sufficiently representative training data. With this usually being limited, current solutio…

cs.IR2022★ 22 cited

S-Walk: Accurate and Scalable Session-based Recommendationwith Random Walks

Minjin Choi, Jinhong Kim, Joonsek Lee +2

Session-based recommendation (SR) predicts the next items from a sequence of previous items consumed by an anonymous user. Most existing SR models focus only on modeling intra-sess…