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

21 citations · 45 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20234 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.CL20234 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.CL202321 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.CL202314 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.CL2022

BEIKE NLP at SemEval-2022 Task 4: Prompt-Based Paragraph Classification for Patronizing and Condescending Language Detection

Yong Deng, Chenxiao Dou, Liangyu Chen +4

PCL detection task is aimed at identifying and categorizing language that is patronizing or condescending towards vulnerable communities in the general media.Compared to other NLP…

cs.CL20222 cited

To Answer or Not to Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning

Yunjie Ji, Liangyu Chen, Chenxiao Dou +2

Machine Reading Comprehension with Unanswerable Questions is a difficult NLP task, challenged by the questions which can not be answered from passages. It is observed that subtle l…