48 citations · 70 across the 11 of their papers we have counts for
5 papers · 1 filter
SCStory: Self-supervised and Continual Online Story Discovery
Susik Yoon, Yu Meng, Dongha Lee +1
We present a framework SCStory for online story discovery, that helps people digest rapidly published news article streams in real-time without human annotations. To organize news…
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning
Doyoung Kim, Susik Yoon, Dongmin Park +4
In real-world continual learning (CL) scenarios, tasks often exhibit intricate and unpredictable semantic shifts, posing challenges for fixed prompt management strategies which are…
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…
MEGClass: Extremely Weakly Supervised Text Classification via Mutually-Enhancing Text Granularities
Priyanka Kargupta, Tanay Komarlu, Susik Yoon +2
Text classification is essential for organizing unstructured text. Traditional methods rely on human annotations or, more recently, a set of class seed words for supervision, which…
PDSum: Prototype-driven Continuous Summarization of Evolving Multi-document Sets Stream
Susik Yoon, Hou Pong Chan, Jiawei Han
Summarizing text-rich documents has been long studied in the literature, but most of the existing efforts have been made to summarize a static and predefined multi-document set. Wi…