最近,一篇名为 Stealing Reasoning Traces from Proprietary LLM APIs 的文章引发了广泛讨论。顾名思义,这篇文章提出了一种从闭源 LLM API 中提取 reasoning trace(思维链)的方法。

这篇文章挺有意思的,虽然有些标题党,但给很多人增长了见识,这里就简单聊聊。

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介绍英语发音,包括音标、英语元音以及特殊发音规则。本文以通用美式英语(General American, GA)为例。

参考资料:

  1. General American from teflpedia
  2. General American from wikipedia

Youtube channels are also helpful, such as [@rachelenglish](https://www.youtube.com/@rachelsenglish).

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Sources:

  1. original diffusion model 2015 paper by Jascha Sohl-Dickstein
  2. DDPM 2020 paper
  3. Improved DDPM 2021 paper
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这两年代理软件管得比较严,但 ChatGPT 对科研和学习又不可或缺。通常的解决办法是找更稳定的代理节点,也就是俗称的“机场”。不过,如果你手上有一台本身已经能访问外网的远程服务器(别管是怎么来的),也可以换一种思路:让本机通过 SSH 连接这台服务器,再把它作为本机的网络出口。这样一来,本机访问网站时,流量会先走到服务器,再由服务器访问目标网站。

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Straight-through estimator, or STE, is a trick for training models that contain non-differentiable operations, notably the quantization operation commonly used in VQ-VAE.

The core idea is:

Use the non-differentiable operation in the forward pass, but replace its gradient with a simple surrogate in the backward pass.

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Straight-through Gumbel-softmax is a trick for training models with discrete latent variables, similar to the famoud straight through estimator (STE) trick used in VQ-VAE.

The problem is simple:

We want to sample a discrete category in the forward pass, but we still want gradients to flow through it in the backward pass.

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本文介绍 DJI Mic Mini 一代的使用方式,对二代及其他版本也适用。

Sources:

  1. 大疆官方的 Mic Mini 使用方法讲解
  2. DJI Mic Mini
  3. DJI Mic Mini 常见问题
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