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MCPGuard is presented, an automated LLM-based framework for detecting specification-to-SDK conformance gaps and complements conventional endpoint-oriented conformance suites by making SDK conformance of specification constraints directly testable.
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.
MaP provides a simple and effective solution for enhancing motion-centric video reasoning without model training or architectural modification, and consistently improves average motion-reasoning accuracy.
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