2022年5月1日 · We describe this neuro-symbolic architecture, dubbed the Modular Reasoning, Knowledge and Language (MRKL, pronounced "miracle") system, some of the technical challenges in implementing it, and Jurassic-X, AI21 Labs' MRKL system implementation. Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?)

2019年5月1日 · In this paper, we propose a multi-source knowledge representation learning (MKRL) model, which can combine entity descriptions, hierarchical types, and textual relations with triple facts. Specifically, for entity descriptions, a convolutional neural network is used to get representations.

2025年1月7日 · To address this challenges, we propose the Multi-view Knowledge Representation Learning (MKRL) framework for personalized news recommendation, which leverages a multi-view news...

Starting from today, I am retired. But what should I be doing? I neither have the skills, nor the mind to do business, my only advantage is this pair of hands which have taken this world. What a headache… Note: The usage of the term 'retired' here doesn't mean retiring from old age, work etc. It's a specific term to refer to not involving oneself in the affairs of a certain society.

2019年5月1日 · To learn optimized representations of entities and relations in a KG, we propose multi-source knowledge representation learning (MKRL) model to combine triple fact information with rich information in entity descriptions, hierarchical types, and textual relations.

2021年9月29日 · Multi-modal KRL methods aim to learn representations of entities and relationships from multi-modal knowledge graphs. Furthermore, the learned representations can be used to compute the semantic correlations of multi-modal KGs and accomplish KG tasks, e.g., link prediction, triple classification.

2023年7月12日 · 模块化推理、知识和语言系统（MRKL）是一种旨在改进现有大规模 语言模型 的系统。 它尝试将 神经网络 模型（如大规模语言模型LLM）与外部 知识库 以及过去流行的符号专家系统相结合，以兼顾神经模型和符号推理能力。 当前的大规模语言模型（例如GPT-3和Jurassic-1）通常通过两种极端方式应用于多个下游任务： 首先，一种方式是进行零样本学习，即直接将多个任务输入 模型 进行推理，无需更新任何参数。 这种方法保证了模型的多功能性，在不损失 …

MKR is a M ulti-task learning approach for K nowledge graph enhanced R ecommendation. MKR consists of two parts: the recommender system (RS) module and the knowledge graph embedding (KGE) module.

We describe this neuro-symbolic architecture, dubbed the Modular Reasoning, Knowledge and Lan-guage (MRKL, pronounced “miracle”) system, some of the technical challenges in implementing it, and Jurassic-X, AI21 Labs’ MRKL system implementation.

mkrl has 51 repositories available. Follow their code on GitHub.