AI systems are increasingly involved in decisions and actions that may later require investigation. When an AI related incident occurs, investigators need to reconstruct what the system did, why it behaved that way, and which part of the system or supply chain contributed to the outcome.
arXiv:2607. 05428v1 Announce Type: cross Abstract: We present Charlie, an on-premise multi-agent Retrieval-Augmented Generation (RAG) system for structured evidential processing in digital forensic environments.
By Leandro D. Carneiro, Andre L. S. Meirelles, Juliano de A. Gomes, Rafael C. A. Cabral
arXiv:2608. 11274v1 Announce Type: cross Abstract: The dominant paradigm treats AI safety as a property to be instilled during model training via RLHF, DPO, or Constitutional AI.
By Albus W. Ng, Yi Han, Jusheng Zhang, Wenhao Wang
arXiv:2607. 19292v1 Announce Type: cross Abstract: Current AI safety discourse still focuses disproportionately on visible failures, including obvious harms, dramatic misuse, and hypothetical catastrophic scenarios.
By Gjergji Kasneci, Enkelejda Kasneci
arXiv:2606. 04990v1 Announce Type: cross Abstract: Large language model (LLM)-based agents increasingly solve complex tasks by interacting with external tools, retrieval systems, memory modules, environments, and other agents.
By Yiqi Wang, Jiaqi Zhang, Taotao Cai, Zirui Liu, Qingqiang Sun, Zequn Sun, Zhangkai Wu, Mingkai Zhang, Yanming Zhu
arXiv:2606. 29437v1 Announce Type: cross Abstract: The growing use of Large Language Models (LLMs) in education, software engineering, academic writing, and technical documentation raises a key question: how can we evaluate not only AI-assisted outputs, but also the interaction process that produced them?
By Mohammed Bousmah
arXiv:2410. 22526v2 Announce Type: replace Abstract: To effectively address potential harms from Artificial Intelligence (AI) systems, it is essential to identify and mitigate system-level hazards.
By Shalaleh Rismani, Roel Dobbe, AJung Moon
arXiv:2608. 13867v1 Announce Type: cross Abstract: AI coding agents are commonly evaluated as models but deployed as systems.
By Stephanie Jarmak
arXiv:2608. 16775v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly being deployed in cybersecurity operations to assist cybersecurity analysts with rapid decision-making against emerging threats.
By Reza Fayyazi, Michael Zuzak, Shanchieh Jay Yang
arXiv:1912. 08786v3 Announce Type: replace-cross Abstract: Three generations of software have transformed the role of artificial intelligence in society.
By Thomas Bartz-Beielstein
arXiv:2606. 18532v1 Announce Type: cross Abstract: AI systems are increasingly evaluated in bounded environments that combine isolation, simulation, instrumentation, supervision, and evidence capture.
By Inderjeet Singh, Haitham Mahmoud, Andr\'es Murillo
arXiv:2607. 01248v1 Announce Type: cross Abstract: Large language models are increasingly used for knowledge acquisition, code generation, academic writing, and agent-based automation.
By Yang Zhao, Yingshuo Li, Zeyu Zhang