32 citations · 109 across the 18 of their papers we have counts for
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Scientific Explanation and Natural Language: A Unified Epistemological-Linguistic Perspective for Explainable AI
Marco Valentino, André Freitas
A fundamental research goal for Explainable AI (XAI) is to build models that are capable of reasoning through the generation of natural language explanations. However, the methodol…
Similarity-Based Equational Inference in Physics
Jordan Meadows, André Freitas
Automating the derivation of published results is a challenge, in part due to the informal use of mathematics by physicists, compared to that of mathematicians. Following demand, w…
ExplanationLP: Abductive Reasoning for Explainable Science Question Answering
Mokanarangan Thayaparan, Marco Valentino, André Freitas
We propose a novel approach for answering and explaining multiple-choice science questions by reasoning on grounding and abstract inference chains. This paper frames question answe…
Unification-based Reconstruction of Multi-hop Explanations for Science Questions
Marco Valentino, Mokanarangan Thayaparan, André Freitas
This paper presents a novel framework for reconstructing multi-hop explanations in science Question Answering (QA). While existing approaches for multi-hop reasoning build explanat…
Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks
Mokanarangan Thayaparan, Marco Valentino, Viktor Schlegel +1
Recent advances in reading comprehension have resulted in models that surpass human performance when the answer is contained in a single, continuous passage of text. However, compl…
On the Semantic Interpretability of Artificial Intelligence Models
Vivian S. Silva, André Freitas, Siegfried Handschuh
Artificial Intelligence models are becoming increasingly more powerful and accurate, supporting or even replacing humans' decision making. But with increased power and accuracy als…