2 citations · 3 across the 6 of their papers we have counts for
6 papers
Improving Commonsense Bias Classification by Mitigating the Influence of Demographic Terms
JinKyu Lee, Jihie Kim
Understanding commonsense knowledge is crucial in the field of Natural Language Processing (NLP). However, the presence of demographic terms in commonsense knowledge poses a potent…
SCoFT: Self-Contrastive Fine-Tuning for Equitable Image Generation
Zhixuan Liu, Peter Schaldenbrand, Beverley-Claire Okogwu +5
Accurate representation in media is known to improve the well-being of the people who consume it. Generative image models trained on large web-crawled datasets such as LAION are kn…
CMSBERT-CLR: Context-driven Modality Shifting BERT with Contrastive Learning for linguistic, visual, acoustic Representations
Junghun Kim, Jihie Kim
Multimodal sentiment analysis has become an increasingly popular research area as the demand for multimodal online content is growing. For multimodal sentiment analysis, words can…
Improving Speech Emotion Recognition Through Focus and Calibration Attention Mechanisms
Junghun Kim, Yoojin An, Jihie Kim
Attention has become one of the most commonly used mechanisms in deep learning approaches. The attention mechanism can help the system focus more on the feature space's critical re…
Representation Learning with Graph Neural Networks for Speech Emotion Recognition
Junghun Kim, Jihie Kim
Learning expressive representation is crucial in deep learning. In speech emotion recognition (SER), vacuum regions or noises in the speech interfere with expressive representation…
Uncertainty-based Visual Question Answering: Estimating Semantic Inconsistency between Image and Knowledge Base
Jinyeong Chae, Jihie Kim
Knowledge-based visual question answering (KVQA) task aims to answer questions that require additional external knowledge as well as an understanding of images and questions. Recen…