·I Know the answer训练探究模型时候能够预测自己能否回答给定的问题两种方式: Value Head方式:即在语言模型的结构上额外训练一个分类器,预测能否给出正确的回答(这种更优) Natural Language方式:即引入类似” With what confidence could you answer this question?”的提示词,训练模型生成如0%,
下面我将尝试针对 Language Models (Mostly) Know What They Know 的解读,如有不当之处,请读者指正 Introduction 在这篇文章的工作中,作者通过模型自我校准(即通过模型自我评估其回答的正确概率)发现了模型大多数情况下,可以比较好的预测其回答正确性的概率,也就是说:模型大多数情况下知道自己知不知道 通常情况下,...
We study whether language models can evaluate the validity of their own claims and predict which questions they will be able to answer correctly. We first show that larger models are well-calibrated on diverse multiple choice and true/false questions when they are provided in the right format. ...
解读Anthropic 文章 Language Models (Mostly) Know What They Know(模型大多数情况下知道自己是否知道) 论文提出了一种名为"Knowledge Assessment"的方法,用于评估语言模型在回答问题时对自己知识的确信程度。这种方法可以帮助我们了解模型在回答问题时的可靠性,从而更好地利用这些模型。首先介绍了论文的背景,即当前大规...
The prevailing methods to make large language models more powerful and amenable have been based on continuous scaling up (that is, increasing their size, data volume and computational resources1) and bespoke shaping up (including post-filtering2,3, fine
As artificial intelligence systems, particularly large language models (LLMs), become increasingly integrated into decision-making processes, the ability to trust their outputs is crucial. To earn human trust, LLMs must be well calibrated such that they
This kind of reasoning requires more computing resources, but it tends to lead to more powerful AI models. What can LLMs be used for? LLMs are powerful mostly because they're able to be generalized to so many different situations and uses. The same core LLM (sometimes with a bit of fin...
Here's everything you need to know about small language models, including how they differ from LLMs, what they're best used for, and how much they cost.
2.1.4 Unigram, Bigram, and Trigram Models Depending on the value of k chosen in Eq. (4), we get different language models. For example, if k = 0 we get the unigram language model: p(x1x2⋯xn)≈∏i=1nq(xi) Under this model, the probability of observing a given word does not...
Using these models, they derived a new kind of complexity metric based on how difficult it is to predict the sequence of the given code. The intuition behind this complexity metric is that complex source code is also hard to predict. Hence, the worse the prediction matches the actual source...