SlimWise: Decoupling Expert Pruning Across Prefill and Decode for Efficient MoE Serving
Paper • 2609.34117 • Published • 12 •
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SlimWise: Decoupling Expert Pruning Across Prefill and Decode for Efficient MoE Serving authored a paper about 21 hours ago
No Token Left Behind: Reliable KV Cache Compression via Importance-Aware
Mixed Precision Quantization authored a paper about 21 hours ago
CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMsOrganizations
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No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization
Paper • 2402.18096 • Published • 1
CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs
Paper • 2512.17970 • Published
Affine-Scaled Attention: Towards Flexible and Stable Transformer Attention
Paper • 2602.23057 • Published
Training-free Dropout Sampling for Semantic Token Acceptance in Speculative Decoding
Paper • 2603.03333 • Published
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
Paper • 2206.09557 • Published
An Investigation of FP8 Across Accelerators for LLM Inference
Paper • 2502.01070 • Published • 3
Faster Inference of LLMs using FP8 on the Intel Gaudi
Paper • 2503.09975 • Published • 1
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gunho1123/Llama-3.1-8B-Instruct-Codegemm-m2v8g128
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