4 papers
Global Consistency Repair for Natural-Language Claim Sets
Paul He, Elke Kirschbaum, Shiva Kasiviswanathan
NLP systems increasingly aggregate claims from retrieved passages, documents, and generated reasoning steps. Yet current factuality methods mostly verify claims individually or com…
QA-Calibration of Language Model Confidence Scores
Putra Manggala, Atalanti Mastakouri, Elke Kirschbaum +2
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 refl…
Estimating Joint Interventional Distributions from Marginal Interventional Data
Sergio Hernan Garrido Mejia, Elke Kirschbaum, Armin Kekić +2
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. To this end, we ext…
Score matching through the roof: linear, nonlinear, and latent variables causal discovery
Francesco Montagna, Philipp M. Faller, Patrick Bloebaum +2
Causal discovery from observational data holds great promise, but existing methods rely on strong assumptions about the underlying causal structure, often requiring full observabil…