A survey that groups efficient video diffusion methods into four paradigms—step distillation, efficient attention, model compression, and cache/trajectory optimization—and outlines open challenges for practical use.
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Dimensional misalignment slows compressed LLMs on GPUs; GAC uses knapsack optimization to achieve full alignment and up to 1.5x speedup on Llama-3-8B while preserving quality.
Fine-tuned recurrent models like Mamba2 produce competitive text embeddings with linear-time constant-memory inference via vertical chunking, outperforming transformers in memory use.
citing papers explorer
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Efficient Video Diffusion Models: Advancements and Challenges
A survey that groups efficient video diffusion methods into four paradigms—step distillation, efficient attention, model compression, and cache/trajectory optimization—and outlines open challenges for practical use.
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Why Smaller Is Slower? Dimensional Misalignment in Compressed LLMs
Dimensional misalignment slows compressed LLMs on GPUs; GAC uses knapsack optimization to achieve full alignment and up to 1.5x speedup on Llama-3-8B while preserving quality.
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Linear-Time and Constant-Memory Text Embeddings Based on Recurrent Language Models
Fine-tuned recurrent models like Mamba2 produce competitive text embeddings with linear-time constant-memory inference via vertical chunking, outperforming transformers in memory use.