Bridging intelligent symbolic agents and sub-symbolic predictors is a long-standing research
goal in AI. Among the recent integration efforts, symbolic knowledge injection (SKI) proposes …

Background: Despite the advancement in eXplainable Artificial Intelligence, the
explanations provided by model-agnostic predictors still call for improvements (ie, lack of …

The field of neuro-symbolic artificial intelligence (NeSy), which combines learning and
reasoning, has recently experienced significant growth. There now are a wide variety of …

Existing agent-based chatbot frameworks need seamless mechanisms to include
explainable dialogic engines within the contextual flow. To this end, this paper presents a …

We propose a novel method to inject symbolic knowledge in form of Datalog formulæ into
neural networks (NN), called KINS (Knowledge Injection via Network Structuring). The idea …

Abstract We propose KILL (Knowledge Injection via Lambda Layer) as a novel method for
the injection of symbolic knowledge into neural networks (NN) allowing data scientists to …

Symbolic knowledge injection (SKI) represents a promising paradigm for bridging symbolic
knowledge and sub-symbolic predictors in intelligent autonomous agents. Given the wide …

We propose a novel method to inject symbolic knowledge in form of Datalog formulæ into
neural networks (NN), called Knowledge Injection via Network Structuring (KINS). The idea …

NeSy4VRD is a multifaceted resource designed to support the development of
neurosymbolic AI (NeSy) research. NeSy4VRD re-establishes public access to the images …

The rapid evolution of machine learning (ML) has led to the widespread adoption of complex
“black box” models, such as deep neural networks and ensemble methods. These models …