Research paper on AI model quantization withdrawn from arXiv

A research paper titled "Depth Registers Unlock W4A4 on SwiGLU: A Reader/Generator Decomposition" was withdrawn from arXiv. The paper explored post-training W4A4 quantization on a 300M-parameter language model, aiming to reduce perplexity errors. It introduced a method called Depth Registers with a hinge loss, which significantly improved quantization results but still left a small gap compared to FP16. AI

RANK_REASON The cluster contains a withdrawn academic paper. [lever_c_demoted from research: ic=1 ai=1.0]

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• Ziyang Liu

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