11 citations · 12 across the 4 of their papers we have counts for
4 papers
Helping Language Models Learn More: Multi-dimensional Task Prompt for Few-shot Tuning
Jinta Weng, Jiarui Zhang, Yue Hu +3
Large language models (LLMs) can be used as accessible and intelligent chatbots by constructing natural language queries and directly inputting the prompt into the large language m…
ConsPrompt: Exploiting Contrastive Samples for Fewshot Prompt Learning
Jinta Weng, Yifan Deng, d Donghao Li +3
The prompt has become an effective linguistic tool for utilizing pre-trained language models. However, in few-shot scenarios, subtle changes in the prompt design always make the re…
STPrompt: Semantic-guided and Task-driven prompts for Effective Few-shot Classification
Jinta Weng, Yue Hu, Jing Qiu +1
The effectiveness of prompt learning has been demonstrated in different pre-trained language models. By formulating suitable template and choosing representative label mapping, pro…
Construction and Application of Teaching System Based on Crowdsourcing Knowledge Graph
Jinta Weng, Ying Gao, Jing Qiu +2
Through the combination of crowdsourcing knowledge graph and teaching system, research methods to generate knowledge graph and its applications. Using two crowdsourcing approaches,…