arXiv:2605. 23922v2 Announce Type: replace-cross Abstract: The EU Artificial Intelligence Act (AIA) establishes a lifecycle governance regime for high-risk AI systems built around ex-ante conformity assessment, post-market monitoring, and re-assessment upon "substantial modification.
By Andrea Ferrario
arXiv:2607. 16130v1 Announce Type: cross Abstract: AI governance increasingly requires judgments about whether an AI system remains adequately trustworthy over time, whether observed changes are tolerable, and how such judgments should be documented in a transparent and contestable way.
By Andrea Ferrario
arXiv:2606. 01444v1 Announce Type: new Abstract: Scientific discovery is not only answer generation but revision of the representational regime in which evidence, artifacts, operations, and verifiers are typed.
By Fiona Y. Wang, Markus J. Buehler
arXiv:2601. 16152v2 Announce Type: replace-cross Abstract: Data systems increasingly operate under persistent legal, political, and analytic disagreement, where no single interpretive authority can be assumed.
By Denise M. Case
arXiv:2607. 18243v1 Announce Type: new Abstract: Agentic AI is crossing trust boundaries faster than current risk models can represent.
By Hassan Karim, Sai Sitharaman, Deepti Gupta, Danda B. Rawat
arXiv:2605. 30169v2 Announce Type: replace-cross Abstract: As autonomous language model agents proliferate, forming an emerging agentic web with real-world consequences, what credibility signals can you use to decide whether to trust an unfamiliar agent in the wild and delegate to it?
By Botao Amber Hu, Helena Rong, Max Van Kleek
arXiv:2608. 11225v1 Announce Type: new Abstract: AI "personality clones" force a re-examination of personal identity in operational terms.
By Luc E. Brunet
arXiv:2607. 18548v1 Announce Type: new Abstract: Agentic artificial intelligence systems, capable of autonomous perception, planning, tool use, and multi-step action, are increasingly proposed for critical engineering domains where decisions carry physical, operational, or economic consequences.
By Omar Al-Refai, Ibrahim Shahbaz, Adam Ali Husseinat, Michael Mandulak, Jaewon Kim, Eman Hammad
arXiv:2607. 03516v1 Announce Type: cross Abstract: Enterprise artificial intelligence is moving from isolated experimentation toward operational dependency across copilots, retrieval-augmented generation systems, autonomous agents, and AI-enabled business workflows.
By Roopam W. Sure
arXiv:2607. 12619v1 Announce Type: new Abstract: The rapid emergence of LLM-powered autonomous and semi-autonomous agents is reshaping software systems from static, request-response components into goal-directed, adaptive, and tool-using computational actors.
By Amin Beheshti, Rong N. Chang, Boualem Benatallah, Fabio Casati, Schahram Dustdar, Geoffrey Fox, Quan Z. Sheng, Yan Wang, Jian Yang, Albert Zomaya
arXiv:2606. 16319v1 Announce Type: new Abstract: Modern AI systems exhibit structural failures that capability scaling alone does not reliably fix: they optimize under-specified objectives with no architectural mechanism to question whether the objective should be optimized at all.
By Edward Y. Chang
arXiv:2606. 30306v1 Announce Type: cross Abstract: Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions.
By Tianyu Ding, Aditya Nannapaneni, Bingfan Liu, Ling Zhang