The Token Not Taken: Sampling, State, and the Variability of AI Agent Outputs 事件

The Token Not Taken: Sampling, State, and the Variability of AI Agent Outputs arXiv:2606.08998v1 Announce Type: new Abstract: Agentic AI systems can behave differently across runs: the same request may produce a different plan, a different tool call, a different code edit, or a different final answer. Such variability arises from several layers that are often conflated. A foundation model is a large pretrained model, usually adaptable to many downstream tasks, that maps an input context to pred