arXiv:2606. 05256v1 Announce Type: new Abstract: This study analyzes a publicly released dataset from a discontinued field experiment on Reddit's r/ChangeMyView.
By Kokil Jaidka, Saifuddin Ahmed
arXiv:2607. 29334v1 Announce Type: cross Abstract: Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as foreign propaganda, with consequences for democratic discourse and information sovereignty.
By Ningzhi Liu, Yannic Hinrichs, Jonas R. Kunst
arXiv:2601. 05050v3 Announce Type: replace Abstract: Large language models (LLMs) have been shown to be persuasive across a variety of contexts.
By Thomas H. Costello, Kellin Pelrine, Matthew Kowal, Jasper Timm, Antonio A. Arechar, Jean-Fran\c{c}ois Godbout, Adam Gleave, David Rand, Gordon Pennycook
arXiv:2608. 15746v1 Announce Type: new Abstract: We present a forensic analysis of the generation pipeline behind a recent AI-driven influence campaign.
By Benjamin Icard, Elouan Vuichard, Louis Lefebvre, Lila Sainero, Thomas Girault, Alice Breton, Tanguy Launay, Gauvain Bourgne, Morgane Casanova, Guillaume Gadek, Victor Kl\"otzer, Michel Le Nouy, Guillaume Gravier, Jean-Gabriel Ganascia, Paul \'Egr\'e
arXiv:2606. 08076v1 Announce Type: cross Abstract: Large Language Models (LLMs) can generate high-quality arguments, yet their ability to engage in nuanced and persuasive communicative actions remains largely unexplored.
By Esra D\"onmez, Agnieszka Falenska
arXiv:2607. 20449v1 Announce Type: cross Abstract: LLMs are trained predominantly on human-authored text, yet the structural and narrative conventions embedded in that text are rarely examined as a source of systematic behavioral influence, or as a governance risk in deployed systems.
By Adam Rigby, Raz Saremi, Azadeh Sohrabinejad, Mehdi Rahimi