Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Active Example Selection for In-Context Learning
Yiming Zhang, Feng Shi, Chenhao Tan
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2022)
Open Access | Times Cited: 48

Showing 1-25 of 48 citing articles:

DB-GPT: Large Language Model Meets Database
Xuanhe Zhou, Zhaoyan Sun, Guoliang Li
Data Science and Engineering (2024) Vol. 9, Iss. 1, pp. 102-111
Open Access | Times Cited: 15
LayoutLLM-T2I: Eliciting Layout Guidance from LLM for Text-to-Image Generation
Leigang Qu, Shengqiong Wu, Hao Fei, et al.
(2023), pp. 643-654
Open Access | Times Cited: 40
Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data
Kashun Shum, Shizhe Diao, Tong Zhang
(2023)
Open Access | Times Cited: 24
CodeS: Towards Building Open-source Language Models for Text-to-SQL
Haoyang Li, Jing Zhang, Hanbing Liu, et al.
Proceedings of the ACM on Management of Data (2024) Vol. 2, Iss. 3, pp. 1-28
Open Access | Times Cited: 11
GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models
Yonggan Fu, Yongan Zhang, Zhongzhi Yu, et al.
2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD) (2023)
Open Access | Times Cited: 18
Prompting Large Language Models for Automatic Question Tagging
Nuojia Xu, Dizhan Xue, Shengsheng Qian, et al.
Deleted Journal (2025)
Closed Access
Active Learning Principles for In-Context Learning with Large Language Models
Katerina Margatina, Timo Schick, Νικόλαος Αλέτρας, et al.
(2023), pp. 5011-5034
Open Access | Times Cited: 12
Enhancing Text-to-SQL Capabilities of Large Language Models: A Study on Prompt Design Strategies
Linyong Nan, Yilun Zhao, Weijin Zou, et al.
(2023), pp. 14935-14956
Open Access | Times Cited: 11
SMOOTHIE: Label Free Language Model Routing
Neel Guha, Mayee F. Chen, Trevor Chow, et al.
(2025)
Open Access
Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval
Jesus Lovon, Martin Mouysset, Jo Oleiwan, et al.
Lecture notes in computer science (2025), pp. 153-168
Closed Access
Towards the Effect of Examples on In‐Context Learning: A Theoretical Case Study
Pengfei He, Yingqian Cui, Han Xu, et al.
Stat (2025) Vol. 14, Iss. 1
Open Access
MARRO: multi-headed attention for rhetorical role labeling in legal documents
Purbid Bambroo, Subinay Adhikary, Paheli Bhattacharya, et al.
Artificial Intelligence and Law (2025)
Closed Access
Document-level event extraction from Italian crime news using minimal data
Giovanni Bonisoli, David Vilares, Federica Rollo, et al.
Knowledge-Based Systems (2025), pp. 113386-113386
Closed Access
One Size Doesn’t Fit All: Predicting the Number of Examples for In-Context Learning
Manish Chandra, Debasis Ganguly, Iadh Ounis
Lecture notes in computer science (2025), pp. 67-84
Closed Access
ALPET: Active few-shot learning for citation worthiness detection in low-resource Wikipedia languages
Aida Halitaj, Arkaitz Zubiaga
Expert Systems with Applications (2025), pp. 127503-127503
Open Access
How Do In-Context Examples Affect Compositional Generalization?
Shengnan An, Zeqi Lin, Qiang Fu, et al.
(2023), pp. 11027-11052
Open Access | Times Cited: 10
Grimoire is All You Need for Enhancing Large Language Models
Ding Chen, Shichao Song, Qingchen Yu, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 3
Large Language Model Instruction Following: A Survey of Progresses and Challenges
Renze Lou, Kai Zhang, Wenpeng Yin
Computational Linguistics (2024), pp. 1-43
Open Access | Times Cited: 3
A Survey of Reasoning with Foundation Models
Jiankai Sun, Chuanyang Zheng, Enze Xie, et al.
(2023)
Open Access | Times Cited: 8
Skill-Based Few-Shot Selection for In-Context Learning
Shengnan An, Bo Zhou, Zeqi Lin, et al.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2023), pp. 13472-13492
Open Access | Times Cited: 7
Improving Probability-based Prompt Selection Through Unified Evaluation and Analysis
Sohee Yang, Jonghyeon Kim, Joel Jang, et al.
Transactions of the Association for Computational Linguistics (2024) Vol. 12, pp. 664-680
Open Access | Times Cited: 2
Retrieval-style In-context Learning for Few-shot Hierarchical Text Classification
Huiyao Chen, Yu Zhao, Zulong Chen, et al.
Transactions of the Association for Computational Linguistics (2024) Vol. 12, pp. 1214-1231
Open Access | Times Cited: 2
Efficient In-Context Medical Segmentation with Meta-Driven Visual Prompt Selection
Chenwei Wu, David Restrepo, Zitao Shuai, et al.
Lecture notes in computer science (2024), pp. 255-265
Closed Access | Times Cited: 2
Data Curation Alone Can Stabilize In-context Learning
Ting-Yun Chang, Robin Jia
(2023), pp. 8123-8144
Open Access | Times Cited: 6
A Survey of Deep Active Learning for Foundation Models
Tianjiao Wan, Kele Xu, Ting Yu, et al.
Intelligent Computing (2023) Vol. 2
Open Access | Times Cited: 6
Page 1 - Next Page

Scroll to top