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Recast is a safety risk forecasting framework that advances LLM safeguarding beyond turn-level violation detection to trajectory-level risk prediction, and demonstrates the effectiveness of trajectory-level forecasting in identifying emerging risks before safety violations occur.
This paper presents a semantic mapping system that integrates Vision-Language Models (VLMs) with Simultaneous Localization and Mapping (SLAM) to enhance the understanding of indoor environments. While traditional SLAM systems primarily focus on geometric occupancy, they often lack the semantic context needed for high-l...
HalluProp, a Propagation-aware Hallucination inference framework that estimates individual agent failures and emergent system-level hallucination risks before inter-agent interaction, and effectively complements post-hoc methods, highlighting the potential of pre-hoc risk inference for building more reliable multi-agen...
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