arXiv:2608. 15304v1 Announce Type: new Abstract: Frontier agentic systems powered by large language models (LLMs) exhibit human-like patterns of cognition.
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:2606. 23991v1 Announce Type: new Abstract: What is an agent?
arXiv:2606. 15485v1 Announce Type: cross Abstract: Agentic AI systems act autonomously, use tools, adapt to context, and operate in complex real-world environments.
arXiv:2609.38486v1 Announce Type: cross Abstract: Large Language Models (LLMs) and more broadly Artificial Intelligence (AI) systems are often described and understood in human-like terms, a phenomen...
arXiv:2608.28518v1 Announce Type: cross Abstract: We investigate whether automatic speech recognition (ASR) errors in user input can lead to unsafe outputs from Embodied AI (EAI) models. We find that...
The article discusses autonomous systems as the pinnacle of AI development, emphasizing the need to blend connectionist and symbolic AI within systems engineering. It introduces a generic agent architecture that organizes behavior around long‑term memory and outlines challenges in linking sensory data to structured memory, goal‑oriented decision making, planning, and agent coordination for collective intelligence. The authors also explore agent trustworthiness, noting it extends beyond behavior to include cognitive validity, and propose methods for its evaluation while highlighting the gap between current capabilities and the envisioned autonomous multi‑agent systems.
arXiv:2509.08494v2 Announce Type: replace-cross Abstract: As humans delegate more tasks and decisions to artificial intelligence (AI), we risk losing control of our individual and collective futures....