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20192023
most citedExploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases

21 citations · 43 across the 4 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2023★ 4 cited

A Comparative Study between Full-Parameter and LoRA-based Fine-Tuning on Chinese Instruction Data for Instruction Following Large Language Model

Xianghui Sun, Yunjie Ji, Baochang Ma +1

Recently, the instruction-tuning of large language models is a crucial area of research in the field of natural language processing. Due to resource and cost limitations, several r…

cs.CL2023★ 4 cited

Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and Evaluation

Yunjie Ji, Yan Gong, Yong Deng +4

Recently, significant public efforts have been directed towards developing low-cost models with capabilities akin to ChatGPT, thereby fostering the growth of open-source conversati…

cs.CL2023★ 21 cited

Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases

Yunjie Ji, Yong Deng, Yan Gong +5

The success of ChatGPT has recently attracted numerous efforts to replicate it, with instruction-tuning strategies being a key factor in achieving remarkable results. Instruction-t…

cs.CL2023★ 14 cited

Exploring ChatGPT's Ability to Rank Content: A Preliminary Study on Consistency with Human Preferences

Yunjie Ji, Yan Gong, Yiping Peng +5

As a natural language assistant, ChatGPT is capable of performing various tasks, including but not limited to article generation, code completion, and data analysis. Furthermore, C…

cs.CL2020

Selective Attention Encoders by Syntactic Graph Convolutional Networks for Document Summarization

Haiyang Xu, Yun Wang, Kun Han +3

Abstractive text summarization is a challenging task, and one need to design a mechanism to effectively extract salient information from the source text and then generate a summary…

cs.CL2019

DELTA: A DEep learning based Language Technology plAtform

Kun Han, Junwen Chen, Hui Zhang +20

In this paper we present DELTA, a deep learning based language technology platform. DELTA is an end-to-end platform designed to solve industry level natural language and speech pro…