arXiv:2606. 08323v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) systems are rapidly emerging, yet transparency, a cornerstone of responsible AI, remains under-defined in these distributed architectures, which have complexities of inter-agent coordination and orchestration.
arXiv:2606. 11116v1 Announce Type: cross Abstract: As newsrooms integrate generative AI, journalists face a disclosure challenge: how to communicate AI involvement in ways that maintain reader trust.
arXiv:2607. 10856v1 Announce Type: cross Abstract: The rise of Software Engineering (SE) agents, i.
arXiv:2606. 30652v1 Announce Type: cross Abstract: Transparency is increasingly mandated for public-sector AI systems, with organisations required to publish statements describing their AI use and oversight arrangements.
arXiv:2606. 05391v1 Announce Type: cross Abstract: Autonomous software agents hold promise to increase developer productivity but make mistakes and exhibit novel failure modes, making human oversight central to successful human-agent collaboration.
arXiv:2606. 26203v1 Announce Type: new Abstract: As AI agent protocols proliferate, the governance structures shaping their interoperability standards remain empirically underexamined.
arXiv:2608. 12104v1 Announce Type: cross Abstract: The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms.
arXiv:2511. 08639v4 Announce Type: replace-cross Abstract: Existing AI disclosure mandates in scholarship require that AI assistance be reported but leave transparency philosophically unspecified: they fix the duty without explaining what the duty serves.
arXiv:2607. 19941v1 Announce Type: cross Abstract: As AI agents become integral to business workflows, establishing guiding user experience (UX) principles is crucial for ensuring user trust and successful adoption.
arXiv:2606. 05608v1 Announce Type: cross Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into static code, and manually adapt that code as requirements evolve.
arXiv:2505. 23847v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership.
arXiv:2505. 11577v5 Announce Type: replace-cross Abstract: Recent application programming interface (API) restrictions on major social media platforms challenge compliance with the EU Digital Services Act [20], which mandates data access for algorithmic transparency.
arXiv:2505. 23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership.