本文主要介绍了一种名为"Inference-Time Intervention (ITI)"的技术,目的是提高大型语言模型的真实性。该技术通过在推理过程中改变模型激活,使激活朝着更加真实的方向移动。ITI技术显著提高了LLaMA模型在TruthfulQA基准测试中的性能。文章还提出了对ITI的优化和应用,并与其他基线方法进行比较和分析。 ·实验背景: 1. ...
读论文Inference-Time Intervention 完整标题:Inference-Time Intervention: Eliciting Truthful Answers from a Language Model 出处:NIPS‘23 哈佛大学 这篇文章阐明了中间层信息和输出层信息之间可能存在差距,即LLM再从中间层过渡到输出层时激活空间中的方向偏离了真实方向。因此,作者提出了一种干预方法,根据激活空间中向...
We propose Inference-Time Intervention (ITI): shifting the activations along the difference of the two distribution means during inference time; model weights are kept intact.The same intervention process is repeated for generation of each token autoregressively. Here’s an example. For the same ...
Zen provided this really cool library called pyvene that can be used to load Inference-time Intervention, and many other mechanistic intervention technique. Here is what he says:pyvene pushes for streamlining the sharing process of inference-time interventions and many more, comparing with other ...
Pearl’s calculus of intervention is complete. In Proc. 22nd Conf. Uncertainty in Artificial Intelligence (UAI’06) (eds Dechter, R. & Richardson, T.) 217–224 (AUAI Press, 2006). Shpitser, I. & Pearl, J. Identification of conditional interventional distributions. In Proc. 22nd Conf. ...
Moreover, in many fields of science, learning the causal structure of dynamic systems and time series data is considered an interesting task which plays an important role in scientific discoveries. Estimating the effect of an intervention and identifying the causal relations from the data can be ...
Collision or convergence?: beliefs and politics in neuroscience discovery, ethics, and intervention. Discovery and interventions for neurological disorders have a unique capacity to galvanize public opinion over issues of access, human rights, decision mak... B Paylor,H Longstaff,F Rossi,... - 《...
Moreover, in many fields of science, learning the causal structure of dynamic systems and time series data is considered an interesting task which plays an important role in scientific discoveries. Estimating the effect of an intervention and identifying the causal relations from the data can be ...
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为了引导LLM正确说出他们知道的内容,学界有尝试用微调+强化学习,但是作者指出,这类方法一需要大量标注数据集,二是需要耗费大量的计算资源,而作者认为,他们提出的Inference-Time Intervention能解决这些问题。 2、工作创新点 正如作者所说,少量的计算资源与少量的数据集是这个方法的巨大优势,并且,这是一种minimally-invasiv...