122 citations · 253 across the 25 of their papers we have counts for
5 papers · 1 filter
LID 2020: The Learning from Imperfect Data Challenge Results
Yunchao Wei, Shuai Zheng, Ming-Ming Cheng +32
Learning from imperfect data becomes an issue in many industrial applications after the research community has made profound progress in supervised learning from perfectly annotate…
Imbalanced Continual Learning with Partitioning Reservoir Sampling
Chris Dongjoo Kim, Jinseo Jeong, Gunhee Kim
Continual learning from a sequential stream of data is a crucial challenge for machine learning research. Most studies have been conducted on this topic under the single-label clas…
Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context
Hankyol Lee, Youngjae Yu, Gunhee Kim
We present a novel data augmentation technique, CRA (Contextual Response Augmentation), which utilizes conversational context to generate meaningful samples for training. We also m…
Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness
Hyunwoo Kim, Byeongchang Kim, Gunhee Kim
We explore the task of improving persona consistency of dialogue agents. Recent models tackling consistency often train with additional Natural Language Inference (NLI) labels or a…
Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue
Byeongchang Kim, Jaewoo Ahn, Gunhee Kim
Knowledge-grounded dialogue is a task of generating an informative response based on both discourse context and external knowledge. As we focus on better modeling the knowledge sel…