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HUGIN, a training framework with two complementary components for Joint Multi-Scene Understanding, supports the practical viability of VLM-based planning for autonomous logistics sorting and provides a high-quality industrial sorting dataset and benchmark.
O2C-Nav is proposed, an efficient zero-shot navigation framework that calls only a single large model once per decision step and introduces a training-free structured waypoint generator and a novel abstract representation that projects sparse, history-aware candidate waypoints directly onto RGB images as visual markers...
ProVisE (Protocolized Visual Evaluation), a benchmark-agnostic framework that elicits protocol-constrained visual answers from image-generation models and parses them into structured predictions compatible with original metrics, is proposed and revealed, revealing complementary strengths of pixel-space expression and t...
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