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English(EN) I spent a week testing whether LLMs can really "program weights." Reading weights: yes. Self-improvement: no. 20 steps of fine-tuning erase the edit

LLM可以读取并应用权重编辑，但修复不是持久的

作者 PulseAugur 编辑部 · [1 个来源] ·

最近的一项实验探索了大语言模型（LLM）修改自身内部权重的能力，发现虽然模型可以读取和应用权重编辑，但这些更改并非持久的。测试表明，LLM可以成功修复错误并应用特定修改，例如减少捏造的传记，但这些改进在标准的微调过程中会被完全抹去。这表明当前的LLM可以作为冻结模型的临时修补程序，但真正的自我改进取决于开发通过训练使这些编辑永久化的方法。 AI

影响 当前的LLM可以临时修补问题，但真正的自我改进需要通过训练使编辑持久化。

排序理由 该集群详细介绍了关于LLM内部权重修改和自我改进能力的实验结果。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/singularity 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

LLM可以读取并应用权重编辑，但修复不是持久的

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该集群详细介绍了关于LLM内部权重修改和自我改进能力的实验结果。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. r/singularity TIER_2 English(EN) · /u/kevinpl07 ·

    I spent a week testing whether LLMs can really "program weights." Reading weights: yes. Self-improvement: no. 20 steps of fine-tuning erase the edit

    <table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1xpip7q/i_spent_a_week_testing_whether_llms_can_really/"> <img alt="I spent a week testing whether LLMs can really &quot;program weights.&quot; Reading weights: yes. Self-improvement: no. 20 steps of fine-tun…

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