Unverified50% confidenceFactExact time
This study proposes using a supervised large language model (LLM) for late fusion, aggregating the outputs of heterogeneous echocardiography AI models in language space, eliminating the need for format conversion and feature engineering for each individual model.
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50%
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Long-term
Relevance
10/30/2026
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Unverified离散扩散语言模型主流方案包括：将token映射到连续嵌入空间进行扩散（如Diffusion-LM），或设计离散扩散过程用掩码模拟加噪（如D3PM、MDLM）77% similarUnverifiedThe architectural core of a multimodal large model must include a large language model (LLM) as its backbone.76% similarUnverifiedFor tools that go from natural language to executable models, feasible approaches usually involve adding a validation layer after LLM parsing, or providing a manual correction interface.74% similarUnverifiedA recent paper proposes directly coupling the continuous latent space framework to continuous diffusion language models (dLLMs), replacing random mapping with a learned language distribution to generate more natural adversarial prompts.74% similar
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