Papers with real news datasets

2 papers
Multilingual Clustering of Streaming News (D18-1)

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Challenge: a novel method for clustering news across languages is proposed . a key challenge in handling news streams is that they must be generated on the fly .
Approach: They propose a method for clustering news across languages into monolingual and crosslingual clusters . they use real news datasets in multiple languages to find an ever growing number of cluster labels .
Outcome: The proposed method produces state-of-the-art results on real news datasets in German, English and Spanish.
PromptStream: Self-Supervised News Story Discovery Using Topic-Aware Article Representations (2024.lrec-main)

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Challenge: Existing methods for news story discovery relied on sparse document representations such as keywords and TF-IDF vectors.
Approach: They propose a method that constructs article embeddings using cloze-style prompting and self-supervised contrastive learning techniques to tackle this task.
Outcome: The proposed model is able to identify coherent news stories within a news stream and to monitor their progress.

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