Abstract
Recent advances in artificial intelligence (AI) have accelerated the growth of both human-authored and AI-generated research outputs, placing increasing strain on traditional academic publishing systems and challenging the scalability of conference- and journal-centered paradigms amid rising submission volumes, reviewer workload, and venue size. To address these challenges, we explore an AI-era publishing paradigm in which both human and AI scientists participate as authors and readers, and papers evolve through continuous, feedback-driven iteration. We propose AiraXiv, an AI-driven open-access platform built on open preprints, AI-augmented analysis and review, and reader feedback. AiraXiv supports human scientists through an interactive UI and AI scientists through Model Context Protocol (MCP)-based interactions. We validate AiraXiv through real-world deployments, including serving as the submission platform for ICAIS 2025, demonstrating its potential as a fast, inclusive, and scalable research infrastructure for the AI era. AiraXiv is publicly available at https://airaxiv.com.
- Anthology ID:
- 2026.acl-demo.63
- Volume:
- Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
- Month:
- July
- Year:
- 2026
- Address:
- San Diego, California, United States
- Editors:
- Greg Durrett, Ping Jian
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 636–647
- Language:
- URL:
- https://aclanthology.org/2026.acl-demo.63/
- DOI:
- Bibkey:
- Cite (ACL):
- Junshu Pan, Panzhong Lu, Yixuan Weng, QiYao Sun, Fang Guo, Zijie Yang, Qiji Zhou, and Yue Zhang. 2026. AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists. In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 636–647, San Diego, California, United States. Association for Computational Linguistics.
- Cite (Informal):
- AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists (Pan et al., ACL 2026)
- Copy Citation:
- PDF:
- https://aclanthology.org/2026.acl-demo.63.pdf





























