SMARTLANGUAGEKNOWLEDGEIn this paper,we introduce the large language model and domain-specific model collaboration(LDMC)framework designed to enhance smart education.The LDMC framework leverages the comprehensive and versatile knowledge of large domain-general models,combines it with the specialized and ...
Domain-specific Large Language Models are designed to address the limitations of Generic LLMs in specialized fields. Unlike their generic counterparts, which are trained on a wide array of text sources to develop a broad understanding applicable across multiple domains, a domain-specific LLM focuses ...
DARWIN Series: Domain Specific Large Language Models for Natural Science Emerging tools bring forth fresh approaches to work, and the field of natural science is no different. In natural science, traditional manual, serial, and labour-intensive work is being augmented by automated, parallel, and ...
In this article, we present FAMILIAR a Domain-Specific Language (DSL) that is dedicated to the large scale management of feature models and that complements existing tool support. The language provides a powerful support for separating concerns in feature modeling, through the provision of ...
原文链接: 2311.06503 (arxiv.org)Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering 大语言模型在特定领域问答中的知识偏好对齐 AbstractDeploying large language models (L…
Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing assumption is that eve...
Patsnap Open Platform provides global intellectual property data, drug data, antigen-antibody data, corporate IP data, and more. Additionally, Patsnap offers AI features for various use cases, supporting both API integration and on-premise deployment. Wi
Large language models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks. However, their performance in domain-specific contexts, such as E-learning, is hindered by the lack of specific domain knowledge. This pa
Pretraining Large Language Models (LLMs) on large corpora of textual data is now a standard paradigm. When using these LLMs for many downstream applications, it is common to additionally bake in new knowledge (e.g., time-critical news, or private domain knowledge) into the pretrained model ...
One aspect of this integration is that the expressions in the language—models—must be converted into a form that is executable by the platform. This aspect is straightforward if the platform is designed to directly interpret the models. More commonly, however, it is necessary to transform the...