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Found 9 papers, 5 papers with code
Multilingual End to End Entity Linking
Entity Linking is one of the most common Natural Language Processing tasks in practical applications, but so far efficient end-to-end solutions with multilingual coverage have been lacking, leading to complex model stacks.
Entity Tagging: Extracting Entities in Text Without Mention Supervision
Detection and disambiguation of all entities in text is a crucial task for a wide range of applications.
Open Vocabulary Extreme Classification Using Generative Models
To develop systems that simplify this process, we introduce the task of open vocabulary XMC (OXMC): given a piece of content, predict a set of labels, some of which may be outside of the known tag set.
Multilingual Autoregressive Entity Linking
Moreover, in a zero-shot setting on languages with no training data at all, mGENRE treats the target language as a latent variable that is marginalized at prediction time.
Ranked #2 on
Entity Disambiguation
on Mewsli-9
(using extra training data)
STANCY: Stance Classification Based on Consistency Cues
Controversial claims are abundant in online media and discussion forums.
DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning
Misinformation such as fake news is one of the big challenges of our society.
Exploring Latent Semantic Factors to Find Useful Product Reviews
In this work, we attempt to automatically identify review quality in terms of its helpfulness to the end consumers.
