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DiffLUT-Net is presented, an FPGA-native network connected by six-input LUTs that are trained from scratch, demonstrating the effectiveness of jointly learning LUT functions and sparse connectivity for compact FPGA-native inference.
CompressKV achieves over 97% performance retention with just 3% of the KV cache, revolutionizing resource efficiency in long-context LLMs.
