Skeleton-of-Thought: Large Language Models Can Do Parallel Decoding
Paper
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2307.15337
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Published
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36
Papers from the NICS-EFFALG Team
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DiTFastAttn: Attention Compression for Diffusion Transformer Models
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ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
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Can LLMs Learn by Teaching? A Preliminary Study
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MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression
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MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization
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Evaluating Quantized Large Language Models
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A Survey on Efficient Inference for Large Language Models
Paper • 2404.14294 • Published • 2 -
Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Paper • 2412.17153 • Published • 29