Papers by Nick Beauchamp

2 papers
Generative Entity-to-Entity Stance Detection with Knowledge Graph Augmentation (2022.emnlp-main)

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Challenge: a new task is needed to understand the interaction between entities when inferring stances.
Approach: They propose a task that primes models to identify entities in their canonical names and discern stances jointly.
Outcome: The proposed model outperforms strong comparisons by large margins.
Sentence-level Media Bias Analysis Informed by Discourse Structures (2022.emnlp-main)

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Challenge: Recent work on detecting media bias at the level of individual articles is limited to single sentences.
Approach: They propose to use a news discourse structure and PDTB discourse relations to identify bias sentences within an article that can illuminate and explain the overall bias of the entire article.
Outcome: The proposed model can detect bias at the level of individual articles and a single sentence can explain it.

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