4 accepted papers
Modern LLM-powered autonomous agents increasingly rely on rich user interface (UI) state observations to achieve reliable action grounding in complex digital environments. However, many deployments transmit the full UI state to remote inference servers even when most elements are irrelevant to the c…
In cluttered, unknown, and partially observable environments, Unmanned Aerial Vehicle (UAV) navigation encounters formidable challenges. To address these challenges, we propose an innovative spatio-temporal attention fusion navigation framework called STAF-Navi. The framework integrates spatio-tempo…
The integration of external tools has substantially expanded the capabilities of large language model (LLM) agents, but also introduced new attack surfaces beyond prompt injection. In particular, cross-tool description poisoning can manipulate planner-visible tool metadata to steer an agent’s trajec…
In cluttered, unknown, and partially observable environments, Unmanned Aerial Vehicle (UAV) navigation encounters formidable challenges. To address these challenges, we propose an innovative spatio-temporal attention fusion navigation framework called STAF-Navi. The framework integrates spatio-tempo