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Found 5 papers, 0 papers with code
$β$-calibration of Language Model Confidence Scores for Generative QA
To use generative question-and-answering (QA) systems for decision-making and in any critical application, these systems need to provide well-calibrated confidence scores that reflect the correctness of their answers.
Estimating Joint interventional distributions from marginal interventional data
In this paper we show how to exploit interventional data to acquire the joint conditional distribution of all the variables using the Maximum Entropy principle.
Causal Information Splitting: Engineering Proxy Features for Robustness to Distribution Shifts
Statistical prediction models are often trained on data from different probability distributions than their eventual use cases.
Causal analysis of Covid-19 Spread in Germany
In this work, we study the causal relations among German regions in terms of the spread of Covid-19 since the beginning of the pandemic, taking into account the restriction policies that were applied by the different federal states.
Selecting causal brain features with a single conditional independence test per feature
We propose a constraint-based causal feature selection method for identifying causes of a given target variable, selecting from a set of candidate variables, while there can also be hidden variables acting as common causes with the target.
