AI全流程参与学术会议，实现智能科研协作。
HIKMA: Human-Inspired Knowledge by Machine Agents through a Multi-Agent Framework for Semi-Autonomous Scientific Conferences
- 构建多智能体框架，实现论文生成到发布全流程自动化。
- 支持智能审稿与修订，保持学术透明与版权安全。
- 探索人机协同科研新模式，适合关注AI辅助研究的学者。
HIKMA半自治学术会议是将人工智能深度融入学术出版与展示流程的首次实验。本文介绍并评估了HIKMA框架的设计、实现与效果，涵盖AI数据集构建、基于AI的论文生成、AI辅助同行评审、AI驱动的修改、AI会议展示及AI归档传播。通过结合语言模型、结构化研究流程与领域防护机制，该框架展示了人工智能如何在保障知识产权、透明度与学术完整性的前提下，辅助而非取代传统科研实践。会议作为测试平台和概念验证，揭示了人工智能赋能学术研究的机遇与挑战，并探讨了AI作者权、责任归属及人机协作在科研中的角色。
原文摘要 · Abstract (English)
HIKMA Semi-Autonomous Conference is the first experiment in reimagining scholarly communication through an end-to-end integration of artificial intelligence into the academic publishing and presentation pipeline. This paper presents the design, implementation, and evaluation of the HIKMA framework, which includes AI dataset curation, AI-based manuscript generation, AI-assisted peer review, AI-driven revision, AI conference presentation, and AI archival dissemination. By combining language models, structured research workflows, and domain safeguards, HIKMA shows how AI can support - not replace traditional scholarly practices while maintaining intellectual property protection, transparency, and integrity. The conference functions as a testbed and proof of concept, providing insights into the opportunities and challenges of AI-enabled scholarship. It also examines questions about AI authorship, accountability, and the role of human-AI collaboration in research.
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