Inference-Time Intervention:推理时间干预 Autoregressive 自回归:自回归模型(AR模型)是一种处理时间序列的统计方法,它利用同一变量之前各期的表现情况,来预测该变量本期的表现情况,并假设它们之间存在线性关系 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...
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...
Italiano (Italia) Português (Brasil) Español (España) Español (México) Edit LW - Inference-Time Intervention: Eliciting Truthful Answers from a Language Model by likenneth(2023 Podcast Episode) See agents for this cast & crew on IMDbPro ...
Estimating the effect of an intervention and identifying the causal relations from the data can be performed via causal inference. Existing surveys on time series discuss traditional tasks such as classification and forecasting or explain the details of the approaches proposed to solve a specific task...
Additionally, there might be a known policy intervention/trend break in the middle of the period under study. My questions are: Which models are most suitable for estimating causal relationships in time series data, especially when dealing with trends, autocorrelation, and structural breaks? ...
(what the response would have done if we'd not made an intervention). this is all very familiar to anyone who has worked with causal impact or other extensions of did, however the part that is troubling me is the specification of the model. in the reading around the subject that ...
assumes that the outcome time series can be explained in terms of a set of control time series that were themselves not affected by the intervention. Furthermore, the relation between treated series and control series is assumed to be stable during the post-intervention period. Understanding and ...
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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. In the language ofSteering GPT-2-XL by adding an activation vector, this is an activation addition using the steering ...
However, if any critical deterioration is detected, then the decision of when to take the intervention, given the costs of diagnosis and therapeutics, is of fundamental importance. In this paper, Bayesian inference of a nonhomogeneous Poisson process with power law failure intensity function is ...