| An open source machine learning framework for efficient and transparent systematic reviews R Van De Schoot, J De Bruin, R Schram, P Zahedi, J De Boer, ... Nature machine intelligence 3 (2), 125-133, 2021 | 346 | 2021 |
| Missing information, unresponsive authors, experimental flaws: The impossibility of assessing the reproducibility of previous human evaluations in NLP A Belz, C Thomson, E Reiter, G Abercrombie, JM Alonso-Moral, M Arvan, ... arXiv preprint arXiv:2305.01633, 2023 | 28 | 2023 |
| Assessing the reliability of word embedding gender bias measures Y Du, Q Fang, D Nguyen arXiv preprint arXiv:2109.04732, 2021 | 23 | 2021 |
| Evaluating the construct validity of text embeddings with application to survey questions Q Fang, D Nguyen, DL Oberski EPJ Data Science 11 (1), 39, 2022 | 15 | 2022 |
| ASReview: open source software for efficient and transparent active learning for systematic reviews R van de Schoot, J de Bruin, RD Schram, P Zahedi, J de Boer, ... arXiv preprint ArXiv:2006.12166, 2020 | 14 | 2020 |
| ASReview: active learning for systematic reviews R Van de Schoot, J De Bruin, R Schram, P Zahedi, J De Boer, ... Zenodo, 2021 | 12 | 2021 |
| Approximate measurement invariance of willingness to sacrifice for the environment across 30 countries: The importance of prior distributions and their visualization I Arts, Q Fang, R van de Schoot, K Meitinger Frontiers in Psychology 12, 624032, 2021 | 9 | 2021 |
| On text-based personality computing: Challenges and future directions Q Fang, A Giachanou, A Bagheri, L Boeschoten, EJ van Kesteren, ... arXiv preprint arXiv:2212.06711, 2022 | 8 | 2022 |
| The Role of Time, Weather and Google Trends in Understanding and Predicting Web Survey Response Q Fang, J Burger, R Meijers, K van Berkel Survey Research Methods 15 (1), 2021 | 7 | 2021 |
| Towards adaptive social comparison for education S Sosnovsky, Q Fang, B de Vries, S Luehof, F Wiegant Addressing Global Challenges and Quality Education: 15th European Conference …, 2020 | 6 | 2020 |
| An open source machine learning framework for efficient and transparent systematic reviews. Nature Machine Intelligence, 3 (2), 125-133 R Van De Schoot, J De Bruin, R Schram, P Zahedi, J De Boer, ... | 5 | 2021 |
| An open source machine learning framework for efficient and transparent systematic reviews. Nat Mach Intell. 2021; 3 (2): 125–33 R van de Schoot, J de Bruin, R Schram, P Zahedi, J de Boer, F Weijdema, ... | 5 | |
| Challenges in reproducing human evaluation results for role-oriented dialogue summarization T Ito, Q Fang, P Mosteiro, A Gatt, K van Deemter Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems, 97-123, 2023 | 3 | 2023 |
| Intro to Discrete-Time Survival Analysis in R Q Fang, R Van de Schoot | 2 | 2019 |
| Designing and Evaluating General-Purpose User Representations Based on Behavioral Logs from a Measurement Process Perspective: A Case Study with Snapchat Q Fang, Z Zhou, F Barbieri, Y Liu, L Neves, D Nguyen, DL Oberski, ... arXiv preprint arXiv:2312.12111, 2023 | 1 | 2023 |
| Epicurus at SemEval-2023 Task 4: Improving Prediction of Human Values behind Arguments by Leveraging Their Definitions C Fang, Q Fang, D Nguyen arXiv preprint arXiv:2302.13925, 2023 | 1 | 2023 |
| Modelling Stance Detection as Textual Entailment Recognition and Leveraging Measurement Knowledge from Social Sciences Q Fang, A Giachanou, A Bagheri arXiv preprint arXiv:2212.06543, 2022 | 1 | 2022 |
| PATCH--Psychometrics-AssisTed benCHmarking of Large Language Models: A Case Study of Mathematics Proficiency Q Fang, DL Oberski, D Nguyen arXiv preprint arXiv:2404.01799, 2024 | | 2024 |
| USE: Dynamic User Modeling with Stateful Sequence Models Z Zhou, Q Fang, L Neves, F Barbieri, Y Liu, H Liu, MW Bos, R Dotsch arXiv preprint arXiv:2403.13344, 2024 | | 2024 |
| Effects of Time-Varying Predictors on Web Survey Response Q Fang | | 2019 |
