Cognitive multi-agent system creates persuasive videos like humans
CogenPVG: Cognitive-Enhanced Reflective Multi-Agent Framework for Persuasive Video Generation
MultimediaArtificial Intelligence
Summary
Making videos that can persuade people is hard for computers. The authors created a system called CogenPVG that works like a team of agents, each doing a step like thinking of arguments, planning scenes, making content, and editing. These agents check and improve each other's work using ideas from psychology about how people get convinced. This approach makes videos that feel logical and appealing, much like those made by humans.
What this means in practice
- •For marketing teams: Generate convincing promotional videos tailored to specific topics with improved logical and emotional appeal.$Commercial implications: Enables production of automated persuasive marketing videos that resemble human-crafted content, enhancing engagement and conversion.
- •For content creators: Assist in planning and assembling persuasive video content through AI that mimics human creative workflows.
Authors
Yuntian Xiao, Shoulong Zhang, Wenfeng Song, Yan Wang, Yi Chen, Shuai Li
Abstract
Persuasive video generation (PVG) is a valuable yet under-explored research topic. Despite the significant advances in multimodal content generation, AI-empowered automated creation of human-made-like videos with substantial persuasiveness remains a formidable challenge. In this paper, we propose CogenPVG, a novel Cognitive-Enhanced reflective multi-agent framework tailored for Persuasive Video Generation task. Given the topic and stance from the user, we decouple the sophisticated generation process into four sequential stages: argument reasoning, storyboard planning, asset creation, and post-editing, imitating the workflow of human video producers. To ensure high persuasiveness, each stage is equipped with a pair of generator and critic agents, following a reflective refinement scheme grounded in a solid psychological theory of persuasion, the Elaboration Likelihood Model (ELM). In the argument reasoning stage, we generate highly logical and credible reasoning thoughts under the guidance of critical thinking theory, enabling cognitive enhancement via the central route of the ELM. For the other three stages, we generate and optimize multimodal assets, assembling them into a persuasive video guided by theories of heuristics, as the peripheral route of the ELM. To the best of our knowledge, CogenPVG is the first work focused on general persuasive topics, without being confined to commercial purposes. Extensive experiments and comprehensive analysis demonstrate that our framework achieves the best persuasion performance, thereby proving the effectiveness of our proposed multi-agent framework for the PVG task.