OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction
Xiang Chen, Ningyu Zhang, Xin Xie, et al.
Proceedings of the ACM Web Conference 2022 (2022), pp. 2778-2788
Open Access | Times Cited: 279
Xiang Chen, Ningyu Zhang, Xin Xie, et al.
Proceedings of the ACM Web Conference 2022 (2022), pp. 2778-2788
Open Access | Times Cited: 279
Showing 1-25 of 279 citing articles:
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 9, pp. 1-35
Open Access | Times Cited: 2013
Pengfei Liu, Weizhe Yuan, Jinlan Fu, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 9, pp. 1-35
Open Access | Times Cited: 2013
Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey
Bonan Min, Hayley Ross, Elior Sulem, et al.
ACM Computing Surveys (2023) Vol. 56, Iss. 2, pp. 1-40
Open Access | Times Cited: 558
Bonan Min, Hayley Ross, Elior Sulem, et al.
ACM Computing Surveys (2023) Vol. 56, Iss. 2, pp. 1-40
Open Access | Times Cited: 558
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Hongbin Ye, Ningyu Zhang, Hui Chen, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 459
Hongbin Ye, Ningyu Zhang, Hui Chen, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 459
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 244
Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 244
GPT understands, too
Xiao Liu, Yanan Zheng, Zhengxiao Du, et al.
AI Open (2023) Vol. 5, pp. 208-215
Open Access | Times Cited: 236
Xiao Liu, Yanan Zheng, Zhengxiao Du, et al.
AI Open (2023) Vol. 5, pp. 208-215
Open Access | Times Cited: 236
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification
Shengding Hu, Ning Ding, Huadong Wang, et al.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
Open Access | Times Cited: 175
Shengding Hu, Ning Ding, Huadong Wang, et al.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
Open Access | Times Cited: 175
Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion
Xiang Chen, Ningyu Zhang, Lei Li, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2022), pp. 904-915
Open Access | Times Cited: 100
Xiang Chen, Ningyu Zhang, Lei Li, et al.
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (2022), pp. 904-915
Open Access | Times Cited: 100
A Survey of Knowledge Enhanced Pre-Trained Language Models
Linmei Hu, Zeyi Liu, Ziwang Zhao, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 4, pp. 1413-1430
Open Access | Times Cited: 52
Linmei Hu, Zeyi Liu, Ziwang Zhao, et al.
IEEE Transactions on Knowledge and Data Engineering (2023) Vol. 36, Iss. 4, pp. 1413-1430
Open Access | Times Cited: 52
LLMs for knowledge graph construction and reasoning: recent capabilities and future opportunities
Yuqi Zhu, Xiaohan Wang, Jing Chen, et al.
World Wide Web (2024) Vol. 27, Iss. 5
Closed Access | Times Cited: 52
Yuqi Zhu, Xiaohan Wang, Jing Chen, et al.
World Wide Web (2024) Vol. 27, Iss. 5
Closed Access | Times Cited: 52
Fill in the Blank: Context-aware Automated Text Input Generation for Mobile GUI Testing
Zhe Liu, Chunyang Chen, Junjie Wang, et al.
(2023), pp. 1355-1367
Open Access | Times Cited: 48
Zhe Liu, Chunyang Chen, Junjie Wang, et al.
(2023), pp. 1355-1367
Open Access | Times Cited: 48
CausalKGPT: Industrial structure causal knowledge-enhanced large language model for cause analysis of quality problems in aerospace product manufacturing
Bin Zhou, Xinyu Li, Tianyuan Liu, et al.
Advanced Engineering Informatics (2024) Vol. 59, pp. 102333-102333
Closed Access | Times Cited: 36
Bin Zhou, Xinyu Li, Tianyuan Liu, et al.
Advanced Engineering Informatics (2024) Vol. 59, pp. 102333-102333
Closed Access | Times Cited: 36
Prompting Is All You Need: Automated Android Bug Replay with Large Language Models
Sidong Feng, Chunyang Chen
(2024), pp. 1-13
Open Access | Times Cited: 33
Sidong Feng, Chunyang Chen
(2024), pp. 1-13
Open Access | Times Cited: 33
MINES: Message Intercommunication for Inductive Relation Reasoning over Neighbor-Enhanced Subgraphs
Ke Liang, Lingyuan Meng, Sihang Zhou, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 9, pp. 10645-10653
Open Access | Times Cited: 19
Ke Liang, Lingyuan Meng, Sihang Zhou, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 9, pp. 10645-10653
Open Access | Times Cited: 19
Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions
Zhe Liu, Chunyang Chen, Junjie Wang, et al.
(2024), pp. 1-13
Open Access | Times Cited: 19
Zhe Liu, Chunyang Chen, Junjie Wang, et al.
(2024), pp. 1-13
Open Access | Times Cited: 19
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Ningyu Zhang, Luoqiu Li, Xiang Chen, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 65
Ningyu Zhang, Luoqiu Li, Xiang Chen, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 65
Exploring Task Difficulty for Few-Shot Relation Extraction
Jiale Han, Bo Cheng, Wei Lu
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021), pp. 2605-2616
Open Access | Times Cited: 56
Jiale Han, Bo Cheng, Wei Lu
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021), pp. 2605-2616
Open Access | Times Cited: 56
Good Visual Guidance Make A Better Extractor: Hierarchical Visual Prefix for Multimodal Entity and Relation Extraction
Xiang Chen, Ningyu Zhang, Lei Li, et al.
Findings of the Association for Computational Linguistics: NAACL 2022 (2022)
Open Access | Times Cited: 54
Xiang Chen, Ningyu Zhang, Lei Li, et al.
Findings of the Association for Computational Linguistics: NAACL 2022 (2022)
Open Access | Times Cited: 54
Virtual prompt pre-training for prototype-based few-shot relation extraction
Kai He, Yucheng Huang, Rui Mao, et al.
Expert Systems with Applications (2022) Vol. 213, pp. 118927-118927
Open Access | Times Cited: 49
Kai He, Yucheng Huang, Rui Mao, et al.
Expert Systems with Applications (2022) Vol. 213, pp. 118927-118927
Open Access | Times Cited: 49
Ontology-enhanced Prompt-tuning for Few-shot Learning
Hongbin Ye, Ningyu Zhang, Shumin Deng, et al.
Proceedings of the ACM Web Conference 2022 (2022)
Open Access | Times Cited: 47
Hongbin Ye, Ningyu Zhang, Shumin Deng, et al.
Proceedings of the ACM Web Conference 2022 (2022)
Open Access | Times Cited: 47
Information Retrieval: Recent Advances and Beyond
Kailash Hambarde, Hugo Proença
IEEE Access (2023) Vol. 11, pp. 76581-76604
Open Access | Times Cited: 40
Kailash Hambarde, Hugo Proença
IEEE Access (2023) Vol. 11, pp. 76581-76604
Open Access | Times Cited: 40
Information Screening whilst Exploiting! Multimodal Relation Extraction with Feature Denoising and Multimodal Topic Modeling
Shengqiong Wu, Hao Fei, Yixin Cao, et al.
(2023)
Open Access | Times Cited: 38
Shengqiong Wu, Hao Fei, Yixin Cao, et al.
(2023)
Open Access | Times Cited: 38
Efficient utilization of pre-trained models: A review of sentiment analysis via prompt learning
Kun Bu, Yuanchao Liu, Xiaolong Ju
Knowledge-Based Systems (2023) Vol. 283, pp. 111148-111148
Closed Access | Times Cited: 22
Kun Bu, Yuanchao Liu, Xiaolong Ju
Knowledge-Based Systems (2023) Vol. 283, pp. 111148-111148
Closed Access | Times Cited: 22
GAP: A novel Generative context-Aware Prompt-tuning method for relation extraction
Zhenbin Chen, Zhixin Li, Yufei Zeng, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123478-123478
Closed Access | Times Cited: 13
Zhenbin Chen, Zhixin Li, Yufei Zeng, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123478-123478
Closed Access | Times Cited: 13
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers
Xiaoyan Zhao, Yang Deng, Min Yang, et al.
ACM Computing Surveys (2024) Vol. 56, Iss. 11, pp. 1-39
Open Access | Times Cited: 12
Xiaoyan Zhao, Yang Deng, Min Yang, et al.
ACM Computing Surveys (2024) Vol. 56, Iss. 11, pp. 1-39
Open Access | Times Cited: 12
Prompt Tuning in Biomedical Relation Extraction
Jianping He, Fang Li, Jianfu Li, et al.
Journal of Healthcare Informatics Research (2024) Vol. 8, Iss. 2, pp. 206-224
Closed Access | Times Cited: 11
Jianping He, Fang Li, Jianfu Li, et al.
Journal of Healthcare Informatics Research (2024) Vol. 8, Iss. 2, pp. 206-224
Closed Access | Times Cited: 11
