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Found 5 papers, 1 papers with code
Mapping probability word problems to executable representations
While solving math word problems automatically has received considerable attention in the NLP community, few works have addressed probability word problems specifically.
Understanding ProbLog as Probabilistic Argumentation
ProbLog is a popular probabilistic logic programming language/tool, widely used for applications requiring to deal with inherent uncertainties in structured domains.
smProbLog: Stable Model Semantics in ProbLog for Probabilistic Argumentation
The first contribution of this paper is a novel interpretation of probabilistic argumentation frameworks as probabilistic logic programs.
Efficient Knowledge Compilation Beyond Weighted Model Counting
We introduce Second Level Algebraic Model Counting (2AMC) as a generic framework for these kinds of problems.
SMProbLog: Stable Model Semantics in ProbLog and its Applications in Argumentation
Therefore, the key contribution of this paper are: a more general semantics for ProbLog programs, its implementation into a probabilistic programming framework for both inference and parameter learning, and a novel approach to probabilistic argumentation problems based on such framework.
