Topic
Tsinghua University
2 episodes
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Moonshot AI and Tsinghua Researchers Propose Prfaas a Cross Datacenter Kvcache Architecture That Rethinks How LLMs Are Served at Scale
Justy and Cody unpack PRFaaS, a cross-datacenter KV-cache serving design from Moonshot AI and Tsinghua that tries to make LLM inference less wasteful by treating prefills as reusable networked assets instead of repeating them in every region.
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H Neurons: On the Existence, Impact, and Origin of Hallucination Associated Neurons in LLMs
H-Neurons: On the Existence, Impact, and Origin of Hallucination-Associated Neurons in LLMs Cheng Gao, Huimin Chen, Chaojun Xiao, Zhiyi Chen, Zhiyuan Liu, Maosong Sun Tsinghua University {gaoc24}@mails.tsinghua.edu.cn , {huimchen,xcj,liuzy}@tsinghua.edu.cn Abstract Large language models (LLMs) frequently generate hallucinations – plausible but factually incorrect outputs – undermining their reliability. While prior work has examined hallucinations from macroscopic perspectives such as training data and objectives, the underlying neuron-level mechanisms remain largely unexplored.