21 citations · 109 across the 23 of their papers we have counts for
6 papers · 1 filter
Numerical reasoning in machine reading comprehension tasks: are we there yet?
Hadeel Al-Negheimish, Pranava Madhyastha, Alessandra Russo
Numerical reasoning based machine reading comprehension is a task that involves reading comprehension along with using arithmetic operations such as addition, subtraction, sorting,…
FF-NSL: Feed-Forward Neural-Symbolic Learner
Daniel Cunnington, Mark Law, Alessandra Russo +1
Logic-based machine learning aims to learn general, interpretable knowledge in a data-efficient manner. However, labelled data must be specified in a structured logical form. To ad…
pix2rule: End-to-end Neuro-symbolic Rule Learning
Nuri Cingillioglu, Alessandra Russo
Humans have the ability to seamlessly combine low-level visual input with high-level symbolic reasoning often in the form of recognising objects, learning relations between them an…
PASOCS: A Parallel Approximate Solver for Probabilistic Logic Programs under the Credal Semantics
David Tuckey, Alessandra Russo, Krysia Broda
The Credal semantics is a probabilistic extension of the answer set semantics which can be applied to programs that may or may not be stratified. It assigns to atoms a set of accep…
Discrete Reasoning Templates for Natural Language Understanding
Hadeel Al-Negheimish, Pranava Madhyastha, Alessandra Russo
Reasoning about information from multiple parts of a passage to derive an answer is an open challenge for reading-comprehension models. In this paper, we present an approach that r…
HySTER: A Hybrid Spatio-Temporal Event Reasoner
Theophile Sautory, Nuri Cingillioglu, Alessandra Russo
The task of Video Question Answering (VideoQA) consists in answering natural language questions about a video and serves as a proxy to evaluate the performance of a model in scene…