<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en"><generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator><link href="https://shangzhen-zhu.com/feed.xml" rel="self" type="application/atom+xml"/><link href="https://shangzhen-zhu.com/" rel="alternate" type="text/html" hreflang="en"/><updated>2026-10-19T03:40:11+00:00</updated><id>https://shangzhen-zhu.com/feed.xml</id><title type="html">blank</title><subtitle>Shangzhen Zhu, PhD student at the University of Illinois Urbana-Champaign. Research on how much numerical precision softmax attention in LLMs really needs, and on faster attention kernels. </subtitle><entry><title type="html">How Much Softmax Do You Need in LLMs?</title><link href="https://shangzhen-zhu.com/blog/2026/how-much-softmax/" rel="alternate" type="text/html" title="How Much Softmax Do You Need in LLMs?"/><published>2026-10-18T00:00:00+00:00</published><updated>2026-10-18T00:00:00+00:00</updated><id>https://shangzhen-zhu.com/blog/2026/how-much-softmax</id><content type="html" xml:base="https://shangzhen-zhu.com/blog/2026/how-much-softmax/"><![CDATA[<p>This post lives at <a href="/softmax/">/softmax/</a>.</p>]]></content><author><name></name></author><category term="research"/><category term="softmax"/><category term="attention"/><category term="llm"/><category term="efficiency"/><summary type="html"><![CDATA[What a pretrained LLM needs from softmax, a calibration-free FlashAttention-4 kernel, and what changes when you train with a coarse softmax.]]></summary></entry></feed>