arXiv:2610.03077v1 Announce Type: new Abstract: Propaganda detection is an essential task in natural language processing (NLP), particularly in the context of manipulative political communications. H...
Propaganda detection is an essential task in natural language processing (NLP), particularly in the context of manipulative political communications. However, identifying specific propaganda technique...
The paper introduces UkrMeme, a dataset of 200 Ukrainian wartime memes annotated for persuasive techniques, and PTM-UA, a Ukrainian translation of a subset of the Propaganda 950 benchmark that retains the original visual content. The authors evaluate vision‑language models in a zero‑shot prompting setup across image, text, and multimodal inputs using hierarchical F1 metrics. They also compare Layer‑wise Relevance Propagation and model‑generated token attributions to analyze the semantic categories of evidence emphasized by each explanation method.
arXiv:2610.33464v1 Announce Type: new Abstract: Propagandistic content increasingly circulates through online news and social media, where readers often encounter it with limited scrutiny, highlighti...
The paper investigates how to detect enthymemes—arguments with unstated premises or conclusions—in controversial political tweets about vaccination and immigration. Despite extensive fine‑tuning, models achieve an F1 score of only about 0.67, prompting the authors to propose new evaluation metrics that compare predictions to the full distribution of annotator votes and a model that directly predicts this distribution. The study also shows that models rely on explicit argumentative structure, often missing implicit links that readers must infer, raising concerns for content moderation systems that depend on majority labels.
arXiv:2610.09464v1 Announce Type: new Abstract: Political discourse often uses rhetorical and persuasive language to frame narratives, influence public opinion, and mobilize audiences. While Bangla n...
arXiv:2608. 15746v1 Announce Type: new Abstract: We present a forensic analysis of the generation pipeline behind a recent AI-driven influence campaign.
Enthymemes, arguments with unstated premises or conclusions, are pervasive in persuasive discourse, yet their annotation remains notoriously subjective. We present a resource of 1,482 tweets from politically controversial discourse, annotated by five annotators for the presence of enthymemes and their argument structure, designed to study label variation.
arXiv:2606.12186v2 Announce Type: replace Abstract: Enthymemes, arguments with unstated premises or conclusions, are pervasive in persuasive discourse, yet their annotation remains notoriously subjec...
ARGUS is a new agent-based framework for persuasive argument generation that incorporates a Theory-of-Mind Reasoner to model audience beliefs and values. It uses a component-aware planner to break arguments into subtopics, assign rhetorical functions (logos, pathos, ethos, kairos), and guide evidence retrieval during planning. A refinement module iteratively addresses multi-dimensional weaknesses, and evaluations on three benchmarks show ARGUS outperforming strong baselines and effectively shifting resistant audience stances.
Understanding the social intelligence of large language models (LLMs) is increasingly important for applications involving human-AI interaction and multi-agent environments. Social intelligence compri...
arXiv:2610.20548v1 Announce Type: new Abstract: Understanding the social intelligence of large language models (LLMs) is increasingly important for applications involving human-AI interaction and mul...