Paper recorded by Signals 4 on 2026-09-15 in cs.CL. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16
Category: cs.CL · 自然语言处理 · first seen 2026-09-16
This study investigates the zero-shot ability of large language models (LLMs) to identify and classify hidden narratives in social messages. Our research hypothesis is that LLMs' extensive contextual knowledge allows them to interpret messages on a deeper, pragmatic level, going beyond basic sentiment or topic analysis. Experiments on the Dipromats and SemEval datasets show that providing models w