2 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning
Seongyoon Kim, Gihun Lee, Jaehoon Oh +1
Federated Learning (FL) is a collaborative method for training models while preserving data privacy in decentralized settings. However, FL encounters challenges related to data het…
HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning
Yongjin Yang, Joonkee Kim, Yujin Kim +3
With the proliferation of social media, accurate detection of hate speech has become critical to ensure safety online. To combat nuanced forms of hate speech, it is important to id…
Carpe Diem: On the Evaluation of World Knowledge in Lifelong Language Models
Yujin Kim, Jaehong Yoon, Seonghyeon Ye +4
The dynamic nature of knowledge in an ever-changing world presents challenges for language models trained on static data; the model in the real world often requires not only acquir…
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
Taehyeon Kim, Joonkee Kim, Gihun Lee +1
While instruction-tuned language models have demonstrated impressive zero-shot generalization, these models often struggle to generate accurate responses when faced with instructio…