We show that ProbLog is an instance of a form of Probabilistic Abstract Argumentation (PAA) that builds upon Assumption-Based Argumentation (ABA). The connections pave the way …
Francesca Toni, Nico Potyka, Markus Ulbricht, Pietro Totis
In this paper we tackle the problem of automating the resolution of combinatorics math word problems. We introduce CoLa, a novel declarative language to express combinatorics math …
Pietro Totis, Jesse Davis, Luc De Raedt, Angelika Kimmig
We introduce second level algebraic model counting (2AMC) problems, a framework generalizing several probabilistic inference task. We present a novel Knowledge Compilation …
Rafael Kiesel, Pietro Totis, Angelika Kimmig
We model beliefs in argumentation problems with probabilistic logic programs and show that traditional probabilistic logic programming (PLP) systems cannot reason on this type of …
Pietro Totis, Angelika Kimmig, Luc De Raedt
We analyze different neural models to solve probability math word problems in two ways. First, to predict directly the answer in an end-to-end fashion. Second, to map the text to a …
Simon Suster, Pieter Fivez, Pietro Totis, Angelika Kimmig, Jesse Davis, Luc De Raedt, Walter Daelemans
Answer Set Programming (ASP) is a logic programming language widely used in non-monotonic automated reasoning. Thanks to its popularity, in the last years there has been a great …
Marco De Bortoli, Federico Igne, Fabio Tardivo, Pietro Totis, Agostino Dovier, Enrico Pontelli
We present the first model for argumentation mining for Italian short argumentative texts. We adapted to Italian the software developed by (Peldszus and Stede, 2015) and built a …
Ivan Namor, Pietro Totis, Samuele Garda, Manfred Stede
We present a text classifier that can distinguish Italian news stories from editorials. Inspired by earlier work on English, we built a suitable train/test corpus and implemented a …
Pietro Totis, Manfred Stede