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By harnessing rotational symmetry, this method achieves pose estimation accuracy comparable to traditional techniques, even in the absence of 3D models.
MOSS-Audio achieves state-of-the-art performance in audio understanding tasks by effectively integrating temporal cues and deep acoustic features, setting a new benchmark for audio-language models.
Pathology foundation models excel at clinical tasks, but SpaPath-Bench reveals they differ significantly in their ability to capture the spatial organization of tissues, highlighting a critical gap for spatially-aware applications.
Multimodal models are surprisingly vulnerable to subtle text-based backdoor attacks using common words, making them far more practical and stealthy than previous visual trigger methods.
A multi-agent system can dramatically improve the accuracy of LLM-based housing consultations, jumping from 75% to 95% correctness in real-world scenarios.
Achieve controllable and scalable speech generation with MOSS-TTS, enabling zero-shot voice cloning and long-form synthesis.