SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model

Fuente: arXiv
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Autores principales: Wu, Dayong, Li, Jiaqi, Wang, Baoxin, Zhao, Honghong, Xue, Siyuan, Yang, Yanjie, Chang, Zhijun, Zhang, Rui, Qian, Li, Wang, Bo, Wang, Shijin, Zhang, Zhixiong, Hu, Guoping
Formato: Preprint
Publicado: 2024
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author Wu, Dayong
Li, Jiaqi
Wang, Baoxin
Zhao, Honghong
Xue, Siyuan
Yang, Yanjie
Chang, Zhijun
Zhang, Rui
Qian, Li
Wang, Bo
Wang, Shijin
Zhang, Zhixiong
Hu, Guoping
author_facet Wu, Dayong
Li, Jiaqi
Wang, Baoxin
Zhao, Honghong
Xue, Siyuan
Yang, Yanjie
Chang, Zhijun
Zhang, Rui
Qian, Li
Wang, Bo
Wang, Shijin
Zhang, Zhixiong
Hu, Guoping
contents Large language models (LLMs) have shown remarkable achievements across various language tasks.To enhance the performance of LLMs in scientific literature services, we developed the scientific literature LLM (SciLit-LLM) through pre-training and supervised fine-tuning on scientific literature, building upon the iFLYTEK Spark LLM. Furthermore, we present a knowledge service system Spark Research Assistant (SparkRA) based on our SciLit-LLM. SparkRA is accessible online and provides three primary functions: literature investigation, paper reading, and academic writing. As of July 30, 2024, SparkRA has garnered over 50,000 registered users, with a total usage count exceeding 1.3 million.
format Preprint
id arxiv_https___arxiv_org_abs_2408_06574
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model
Wu, Dayong
Li, Jiaqi
Wang, Baoxin
Zhao, Honghong
Xue, Siyuan
Yang, Yanjie
Chang, Zhijun
Zhang, Rui
Qian, Li
Wang, Bo
Wang, Shijin
Zhang, Zhixiong
Hu, Guoping
Computation and Language
Large language models (LLMs) have shown remarkable achievements across various language tasks.To enhance the performance of LLMs in scientific literature services, we developed the scientific literature LLM (SciLit-LLM) through pre-training and supervised fine-tuning on scientific literature, building upon the iFLYTEK Spark LLM. Furthermore, we present a knowledge service system Spark Research Assistant (SparkRA) based on our SciLit-LLM. SparkRA is accessible online and provides three primary functions: literature investigation, paper reading, and academic writing. As of July 30, 2024, SparkRA has garnered over 50,000 registered users, with a total usage count exceeding 1.3 million.
title SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model
topic Computation and Language
url https://arxiv.org/abs/2408.06574