SOURCE-LINKED INTELLIGENCE

Embedding Models for Stance-Aware Argument Retrieval

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

In computational argumentation, obtaining arguments that explicitly support or attack given claims is a critical precursor to downstream reasoning tasks. When these supporting and attacking arguments are to be retrieved using semantic search methods, they need to be assessed for topic-relevance to the claims of interest as well as for correctness of their (positive or negative) stance towards the claims. In this paper we explore how dense embedding models (hereafter, models), powering modern retrieval pipelines, can serve as the basis of semantic search incorporating this dual assessment. We s

Read original source ↗ Open in workspace

recordType

paper

region

Global