AI系统自主打完整政策辩论，还能赢。
A superpersuasive autonomous policy debating system
- 用多智能体协作架构，分步完成论点构建与反驳。
- 在模拟比赛中胜过人类撰写的辩稿，评委认可度高。
- 支持人机协同辩论，可生成带语音和动画的视频演讲。
人工智能在复杂、基于证据且策略灵活的说服能力方面仍面临巨大挑战。以往工作如IBM Project Debater聚焦于简化版辩论，面向普通观众。我们提出DeepDebater，一个能参与并赢得完整、未经修改的双队政策辩论的自主系统。该系统采用分层多智能体工作流架构，由大语言模型驱动的团队协作完成论证任务，通过大规模政策辩论证据库（OpenDebateEvidence）进行迭代检索、整合与自修正，生成完整发言稿、质询和反驳内容。我们构建了端到端实时交互演示流水线：使用OpenAI TTS将文本转为语音，再通过EchoMimic V1生成说话头视频。系统支持纯AI对战及人机混合模式——人类可随时介入，也可作为对手与AI交锋。初步评估显示，其产出的论点质量优于人类撰写的案例，独立自治裁判判定其在模拟赛中持续获胜；专业辩论教练也更青睐其论证逻辑、证据使用与整体框架。所有代码、生成文本、音频及视频已开源：https://github.com/Hellisotherpeople/DeepDebater/tree/main
原文摘要 · Abstract (English)
The capacity for highly complex, evidence-based, and strategically adaptive persuasion remains a formidable great challenge for artificial intelligence. Previous work, like IBM Project Debater, focused on generating persuasive speeches in simplified and shortened debate formats intended for relatively lay audiences. We introduce DeepDebater, a novel autonomous system capable of participating in and winning a full, unmodified, two-team competitive policy debate. Our system employs a hierarchical architecture of specialized multi-agent workflows, where teams of LLM-powered agents collaborate and critique one another to perform discrete argumentative tasks. Each workflow utilizes iterative retrieval, synthesis, and self-correction using a massive corpus of policy debate evidence (OpenDebateEvidence) and produces complete speech transcripts, cross-examinations, and rebuttals. We introduce a live, interactive end-to-end presentation pipeline that renders debates with AI speech and animation: transcripts are surface-realized and synthesized to audio with OpenAI TTS, and then displayed as talking-head portrait videos with EchoMimic V1. Beyond fully autonomous matches (AI vs AI), DeepDebater supports hybrid human-AI operation: human debaters can intervene at any stage, and humans can optionally serve as opponents against AI in any speech, allowing AI-human and AI-AI rounds. In preliminary evaluations against human-authored cases, DeepDebater produces qualitatively superior argumentative components and consistently wins simulated rounds as adjudicated by an independent autonomous judge. Expert human debate coaches also prefer the arguments, evidence, and cases constructed by DeepDebater. We open source all code, generated speech transcripts, audio and talking head video here: https://github.com/Hellisotherpeople/DeepDebater/tree/main
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