1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2026
When Agents Persuade: Rhetoric Generation and Mitigation in LLMs
Julia Jose, Ritik Roongta, Rachel Greenstadt
Despite their wide-ranging benefits, LLM-based agents deployed in open environments can be exploited to produce manipulative material. In this study, we task LLMs with propaganda o…
cs.CV2026
MLLM-based Textual Explanations for Face Comparison
Redwan Sony, Anil K Jain, Arun Ross
Multimodal Large Language Models (MLLMs) have recently been proposed as a means to generate natural-language explanations for face recognition decisions. While such explanations fa…
cs.CL2025★ 1 cited
Are Large Language Models Good at Detecting Propaganda?
Julia Jose, Rachel Greenstadt
Propagandists use rhetorical devices that rely on logical fallacies and emotional appeals to advance their agendas. Recognizing these techniques is key to making informed decisions…