59 citations · 206 across the 26 of their papers we have counts for
5 papers · 1 filter
Ontology Enrichment for Effective Fine-grained Entity Typing
Siru Ouyang, Jiaxin Huang, Pranav Pillai +3
Fine-grained entity typing (FET) is the task of identifying specific entity types at a fine-grained level for entity mentions based on their contextual information. Conventional me…
Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers
Yu Zhang, Bowen Jin, Xiusi Chen +4
Instead of relying on human-annotated training samples to build a classifier, weakly supervised scientific paper classification aims to classify papers only using category descript…
Unsupervised Story Discovery from Continuous News Streams via Scalable Thematic Embedding
Susik Yoon, Dongha Lee, Yunyi Zhang +1
Unsupervised discovery of stories with correlated news articles in real-time helps people digest massive news streams without expensive human annotations. A common approach of the…
PIEClass: Weakly-Supervised Text Classification with Prompting and Noise-Robust Iterative Ensemble Training
Yunyi Zhang, Minhao Jiang, Yu Meng +2
Weakly-supervised text classification trains a classifier using the label name of each target class as the only supervision, which largely reduces human annotation efforts. Most ex…
Effective Seed-Guided Topic Discovery by Integrating Multiple Types of Contexts
Yu Zhang, Yunyi Zhang, Martin Michalski +3
Instead of mining coherent topics from a given text corpus in a completely unsupervised manner, seed-guided topic discovery methods leverage user-provided seed words to extract dis…