neuro-symbolic

This paper introduces MoE-TLM, a modular architecture for language intelligence based on domain-specialized micro-models coordinated through a neural routing system. In contrast to conventional large language models that rely on massive parameter scaling, the proposed approach distributes intelligence across multiple lightweight expert models, each trained for a specific domain. A central routing…

This Article asks what happens next. The model has encoded its knowledge of fraud as symbolic rules. V14 below a threshold means fraud. What happens when that relationship starts to change? Can the rules act as a canary? In other words: can neuro-symbolic concept drift monitoring work at inference time, without labels? Full architecture background in Hybrid Neuro-Symbolic Fraud Detection: Guiding…

Building Intelligent Agents with Neuro-Symbolic Concepts Author(s) Mao, Jiayuan; Tenenbaum, Joshua; Wu, JiajunAbstract This article presents a concept-centric paradigm for building agents that can learn continually and reason flexibly. The concept-centric agent utilizes a vocabulary of neuro-symbolic concepts. These concepts, such as object, relation, and action concepts, are grounded on sensory …

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