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Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data

AI 摘要

A research paper titled "Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data" has been published on arXiv.org. This paper, categorized under Artificial Intelligence (cs.AI) and Machine Learning (cs.LG), explores methods for generating and adapting weights in Large Language Models using live data. The document, identified as arXiv:2609.18842, was first made available on September 16, 2026, and is associated with Jinli Hu Dr.

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This paper introduces a novel approach to LLM weight generation and adaptation from live data, unlike traditional methods that rely on static datasets.

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收录当时偏移:UTC+02026年9月17日 18:00 UTC

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2026年9月17日 18:00
来源类型
研究
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热度约为该来源近期上榜条目中位水平的 2.0 倍
指标对比
146 vs 中位 73(20 条基线样本)
检出时间
09/18 10:00

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来源·Hacker News·arxiv.org