203 citations · 213 across the 10 of their papers we have counts for
13 papers · 1 filter
Plug-and-Play Adaptation for Continuously-updated QA
Kyungjae Lee, Wookje Han, Seung-won Hwang +3
Language models (LMs) have shown great potential as implicit knowledge bases (KBs). And for their practical use, knowledge in LMs need to be updated periodically. However, existing…
Robustifying Multi-hop QA through Pseudo-Evidentiality Training
Kyungjae Lee, Seung-won Hwang, Sang-eun Han +1
This paper studies the bias problem of multi-hop question answering models, of answering correctly without correct reasoning. One way to robustify these models is by supervising to…
Text Length Adaptation in Sentiment Classification
Reinald Kim Amplayo, Seonjae Lim, Seung-won Hwang
Can a text classifier generalize well for datasets where the text length is different? For example, when short reviews are sentiment-labeled, can these transfer to predict the sent…
KBQA: Learning Question Answering over QA Corpora and Knowledge Bases
Wanyun Cui, Yanghua Xiao, Haixun Wang +3
Question answering (QA) has become a popular way for humans to access billion-scale knowledge bases. Unlike web search, QA over a knowledge base gives out accurate and concise resu…
Categorical Metadata Representation for Customized Text Classification
Jihyeok Kim, Reinald Kim Amplayo, Kyungjae Lee +3
The performance of text classification has improved tremendously using intelligently engineered neural-based models, especially those injecting categorical metadata as additional i…
QADiver: Interactive Framework for Diagnosing QA Models
Gyeongbok Lee, Sungdong Kim, Seung-won Hwang
Question answering (QA) extracting answers from text to the given question in natural language, has been actively studied and existing models have shown a promise of outperforming…