| 1 |
Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting |
提出多模态饮食背景下的CGM预测方法以提升糖尿病管理 |
foundation model multimodal |
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| 2 |
Bidirectional Multimodal Fusion of Sky Images and Time-Series for Solar Forecasting with Large Language Models |
提出SolCloudLLM以解决短期光伏发电预测中的多模态融合问题 |
large language model multimodal |
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| 3 |
CausalArena: Benchmarking Causal Discovery in the Foundation Model Era |
提出CausalArena以解决因果发现评估的多样性问题 |
foundation model |
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| 4 |
Geospatial Foundation Models Capture Health-Relevant Dimensions of Place Beyond Conventional Social Risk Indices |
提出地理基础模型以捕捉健康相关的地理特征 |
foundation model |
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| 5 |
LILA: Calibration-Free Structured Pruning of Large Language Models via Latent Spectral Geometry |
提出LILA以解决大语言模型结构化剪枝中的校准问题 |
large language model |
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| 6 |
The information geometry of large language models is shared, learned, and controllable |
提出几何结构以控制大型语言模型行为 |
large language model |
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| 7 |
Why Does Post-Training Quantization Work? |
探讨后训练量化为何有效以提升大语言模型性能 |
large language model |
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| 8 |
Musec: MomentUm SpEctral Clipping for Stable Muon-type Training |
提出MomentUm SpEctral Clipping以解决Muon训练不稳定问题 |
large language model |
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| 9 |
REVA: Reusable Evidence View Aggregation for Context-Efficient RAG Serving |
提出REVA框架以解决RAG服务中的上下文效率问题 |
large language model |
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| 10 |
EMMI: Edge Multi-Modal Intelligence for Communication-Efficient MLLM Inference via Fused Representation Compression |
提出EMMI以解决边缘设备上多模态大语言模型推理的通信效率问题 |
multimodal |
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