TL;DR
NIKG occupies the space between scene-oriented traffic KGs and intention-prediction models: a small, explicit semantic layer intended to support downstream work such as knowledge graph embedding, SPARQL-based feature extraction, or hybrid neuro-symbolic reasoning.
G-MARK is proposed, a grounded multi-agent reasoning framework that converts cooperative object-centric observations into explicit provenance-aware knowledge graphs (KGs) that preserve object hypotheses together with their source attribution, ego-versus-partner visibility, uncertainty, conflicts, spatial relations, and...
Simulation-based scenario testing is central to the safety validation of autonomous driving systems (ADS), where abstract scenarios must be instantiated into executable concrete scenarios. A key challenge in this process is road matching, which aims to identify a concrete site on a map that genuinely satisfies the road...
A hybrid pipeline for semantic mapping is presented that incorporates an external calibrated camera using homography projection for geometric mapping and localization, combined with object detection, persistent object tracking and ontology driven semantic updates to build a dynamic semantic world model.
A single Triplet Ontological Semantic Model (TOSM) representation is carried across the stack by carrying a single Triplet Ontological Semantic Model (TOSM) representation across the stack so that reasoning, planning, and optimization share one interpretable representation.
This work introduces CASCADE (Causal Spatio-Temporal Analysis of Driving Environments), a structured scene representation for reasoning in driving scenes and a human-annotated dataset built on it that provides the reference for benchmarking the reasoning abilities of Physical AI models, and verifying the quality of aut...
3D grounding aims to localize target entities in complex scenes from natural language and plays a fundamental role in embodied perception and spatial reasoning. However, existing approaches mostly rely on feature similarity or direct matching, making it difficult to connect natural-language intent with the implicit sem...
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