arXiv AI By Wisdom Dogah

Traxia: A Framework for Verifiable, Agent-Native Scientific Publishing

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arXiv:2606. 08256v1 Announce Type: new Abstract: Verifiability, attribution, and reproducibility are foundational requirements of scientific knowledge, yet current publishing infrastructure does not enforce them at scale.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI
Sep 17

Making AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records

The paper introduces Publication Authority, a single-use, non-transferable capability that ensures AI-assisted claims can be independently challenged by providing a machine-readable, falsifiable publication record. It presents the PAC-2026 protocol, evaluates its fourth bounded semantic freeze (SF-4), and demonstrates through extensive modeling that the system enforces strict obligations on evidence, authorization, and lifecycle continuity. The study confirms internal coherence, bounded safety, and fault sensitivity, though it does not address factual truth or field efficacy.

By Torsten Olivi Tiltack, Yifei Dong, Kun Yu, Xu Wang, Wei Liu, Jianlong Zhou, Ren Ping Liu, Fang Chen
arXiv AI
Jun 17

BadScientist: Can a Research Agent Write Convincing but Unsound Papers that Fool LLM Reviewers?

arXiv:2510. 18003v2 Announce Type: replace-cross Abstract: The convergence of LLM-powered research assistants and AI-based peer review systems creates a critical vulnerability: fully automated publication loops where AI-generated research is evaluated by AI reviewers without human oversight.

By Fengqing Jiang, Yichen Feng, Yuetai Li, Luyao Niu, Basel Alomair, Radha Poovendran