Demystifying the Difference Between Explainable AI and Neurosymbolic AI
A practical explanation of how Explainable AI and Neurosymbolic AI differ, where they overlap, and why both matter for trustworthy systems.
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Neurosymbolic AI Articles
Articles on neurosymbolic AI, symbolic regression, rule learning, hybrid neural-symbolic systems, and trustworthy reasoning.
Symbolic Knowledge Distillation of Large Language Models
A clear guide to symbolic knowledge distillation for LLMs, including direct distillation, multilevel distillation, reinforcement learning, and why symbolic outputs matter.
Symbolic regression outperforms other models for small data sets
A practical look at why symbolic regression can be a strong choice when data is scarce, interpretability matters, and overfitting is a constant risk.
Deep Symbolic Regression for Recurrent Sequences
A readable explanation of how Transformers can infer symbolic recurrence relations from integer and float sequences, then use those formulas to extrapolate.
Learning Symbolic Physics with Graph Networks
A readable explanation of how graph networks can learn physical interactions, expose force-like messages, and support symbolic law discovery.
Discovering Symbolic Models from Deep Learning with Inductive Biases
A practical explanation of how symbolic equations can be extracted from trained deep learning models by using inductive biases, sparse latent spaces, graph networks, and symbolic regression.
Symbolic Regression Enhanced Decision Tree
A practical explanation of Symbolic Regression Enhanced Decision Trees, where symbolic regression discovers expressive split rules for compact and interpretable classification trees.
Knowledge Representation and Knowledge Embeddings in Neurosymbolic AI
A practical explanation of symbolic knowledge representations and where that knowledge can be embedded inside neuro-symbolic AI systems.
Neurosymbolic Approaches in Artificial Intelligence
A practical overview of major neuro-symbolic AI approaches, including neural models for symbolic tasks, symbolic knowledge for deep learning, explainability, and hybrid reasoning systems.
Neurosymbolic AI and Trustworthiness
A practical explanation of how neuro-symbolic AI can support trustworthy AI, based on a systematic review of interpretability, fairness, privacy, safety, and symbolic reasoning methods.
Neurosymbolic Reinforcement Learning: An Overview
An accessible overview of neurosymbolic reinforcement learning, explaining how neural learning, symbolic reasoning, and RL can work together to improve interpretability, sample efficiency, reward shaping, pl...
Neurosymbolic AI
An accessible introduction to neurosymbolic AI: why combining neural networks with symbolic reasoning can improve explainability, data efficiency, causal reasoning, and trustworthy decision-making.