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- [ICLR'25] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
CLAP-triangle-counting
PublicThe official code for DATE'23 paper <CLAP: Locality Aware and Parallel Triangle Counting with Content Addressable Memory>MBQ
PublicMoA
PublicThe official implementation of the paper <MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression>- A Behavior-Level Modeling Tool for Memristor-based Neuromorphic Computing Systems
MixDQ
Public[ECCV24] MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision QuantizationRad-NeRF
PublicMoA_project_page
Publiceffgenai-workshop.top
PublicMoA_Kernel
Publicqllm-eval
PublicFlashEval
Publicnicsefc-readme
Publicgibbon
Publicawesome_ai4eda
Public