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Entropy Meets Importance: A Unified Head Importance-Entropy Score for Stable and Efficient Transformer Pruning
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Entropy Meets Importance: A Unified Head Importance-Entropy Score for Stable and Efficient Transformer Pruning
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PermLLM: Learnable Channel Permutation for N:M Sparse Large Language Models
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Fewer Weights, More Problems: A Practical Attack on LLM Pruning
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OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
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OptiFLIDS: Optimized Federated Learning for Energy-Efficient Intrusion Detection in IoT
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Pruning and Distilling LLMs Using NVIDIA TensorRT Model Optimizer
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My Notes From Spark+AI Summit 2020 (Application-Agnostic Talks)
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PATCH: Learnable Tile-level Hybrid Sparsity for LLMs
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Walk and Read Less: Improving the Efficiency of Vision-and-Language Navigation via Tuning-Free Multimodal Token Pruning
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北京内推 | AMD北京AI算法团队招聘模型量化/剪枝算法实习生(可远程)
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EvoP: Robust LLM Inference via Evolutionary Pruning
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ICML 2025 | CoTo:让LoRA训练「渐入佳境」,模型融合、剪枝样样精通
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ICML 2025 | CoTo:让LoRA训练「渐入佳境」,模型融合、剪枝样样精通
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ICLR 2025 | 高效又稳定!人大团队提出模型剪枝新方法LLM-Streamline
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英伟达联手MIT清北发布SANA 1.5,线性扩散Transformer再刷文生图新SOTA
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AutoSculpt: A Pattern-based Automated Pruning Framework Designed to Enhance Efficiency and Accuracy by Leveraging Graph Learning and Deep Reinforcement Learning
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12%计算量就能媲美原模型,Adobe、罗切斯特大学等提出YOPO剪枝技术
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