Abstract The rapid emergence of agentic AI presents new opportunities and challenges for accelerating scientific discovery through tool-augmented reasoning, autonomous workflows, and reproducible results. To explore these capabilities in a hands-on, community-driven setting, we h…
Statistical adversarial detection (SAD) treats detection as a two-sample test. Given a reference set of clean examples (CEs) and a batch of queries, potentially containing an unknown mixture of CEs and adversarial examples (AEs), SAD decides whether the query distribution drifts…
Large language model (LLM) agents have demonstrated strong capability in sequential decision-making, yet they remains fundamentally reactive in long-horizon tasks. Unlike humans who employ "what-if" reasoning to evaluate potential plans before commitment, standard agents lack an…