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We present Hunyuan-A13B, an open-source large language model based on a Mixture-of-Experts architecture. It contains 80 billion total parameters but activates only 13 billion during inference, balancing model capability, computational efficiency, and deployment cost. The model is pretrained on a rigorously filtered 20T...
PixVL is a self-supervised post-training framework that introduces a unified Mask--Text Consistency Cycle, enabling pixel-level MLLMs to generate and self-verify regional descriptions and learn from unlabeled data.
Sarse Multi-Stage Expert-Agent Routing is proposed, a language-based clinical reasoning framework that models diagnosis as a stage-wise routing process and adaptively activates a sparse set of medical expert agents, supported by expert-specific memory across stages.
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