XtraMAC unifies mixed-precision MAC on FPGA via shared integer mantissa products, delivering 1.4-2.0x higher compute density and up to 1.9x better energy efficiency.
Smoothquant: Accurate and efficient post-training quantization for large language models
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
PAD-Rec augments standard draft models with item-position and step-position embeddings plus learnable gates, delivering up to 3.1x wall-clock speedup and 5% average gain over strong speculative-decoding baselines on four datasets while largely preserving recommendation quality.
citing papers explorer
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XtraMAC: An Efficient MAC Architecture for Mixed-Precision LLM Inference on FPGA
XtraMAC unifies mixed-precision MAC on FPGA via shared integer mantissa products, delivering 1.4-2.0x higher compute density and up to 1.9x better energy efficiency.
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Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation
PAD-Rec augments standard draft models with item-position and step-position embeddings plus learnable gates, delivering up to 3.1x wall-clock speedup and 5% average gain over strong speculative-decoding baselines on four datasets while largely preserving recommendation quality.