Advances, challenges and opportunities in creating data for trustworthy AI W Liang, GA Tadesse, D Ho, L Fei-Fei, M Zaharia, C Zhang, J Zou Nature Machine Intelligence 4 (8), 669-677, 2022 | 308 | 2022 |
Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning W Liang, Y Zhang, Y Kwon, S Yeung, JY Zou Advances in Neural Information Processing Systems 35, 17612-17625, 2022 | 302 | 2022 |
GPT detectors are biased against non-native English writers W Liang, M Yuksekgonul, Y Mao, E Wu, J Zou Patterns (2023); arXiv preprint arXiv:2304.02819, 2023 | 282 | 2023 |
Disparities in dermatology AI performance on a diverse, curated clinical image set R Daneshjou, K Vodrahalli, RA Novoa, M Jenkins, W Liang, V Rotemberg, ... Science advances 8 (31), eabq6147, 2022 | 203 | 2022 |
Improving out-of-distribution robustness via selective augmentation H Yao, Y Wang, S Li, L Zhang, W Liang, J Zou, C Finn International Conference on Machine Learning, 25407-25437, 2022 | 181 | 2022 |
Deepstore: In-storage acceleration for intelligent queries VS Mailthody, Z Qureshi, W Liang, Z Feng, SG De Gonzalo, Y Li, H Franke, ... Proceedings of the 52nd Annual IEEE/ACM International Symposium on …, 2019 | 79 | 2019 |
Can large language models provide useful feedback on research papers? A large-scale empirical analysis W Liang, Y Zhang, H Cao, B Wang, DY Ding, X Yang, K Vodrahalli, S He, ... NEJM AI 1 (8), AIoa2400196, 2024 | 71 | 2024 |
Metashift: A dataset of datasets for evaluating contextual distribution shifts and training conflicts W Liang, J Zou ICLR 2022; arXiv preprint arXiv:2202.06523, 2022 | 71 | 2022 |
Monitoring ai-modified content at scale: A case study on the impact of chatgpt on ai conference peer reviews W Liang, Z Izzo, Y Zhang, H Lepp, H Cao, X Zhao, L Chen, H Ye, S Liu, ... arXiv preprint arXiv:2403.07183, 2024 | 67 | 2024 |
Alice: Active learning with contrastive natural language explanations W Liang, J Zou, Z Yu EMNLP 2020; arXiv preprint arXiv:2009.10259, 2020 | 49 | 2020 |
Dawson: A domain adaptive few shot generation framework W Liang, Z Liu, C Liu arXiv preprint arXiv:2001.00576, 2020 | 48 | 2020 |
MOSS: End-to-End Dialog System Framework with Modular Supervision W Liang, Y Tian, C Chen, Z Yu AAAI 2020; arXiv preprint arXiv:1909.05528, 2019 | 44 | 2019 |
GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering W Liang, Y Jiang, Z Liu NAACL MAI 2021;arXiv preprint arXiv:2104.10283, 2021 | 42 | 2021 |
Mapping the increasing use of llms in scientific papers W Liang, Y Zhang, Z Wu, H Lepp, W Ji, X Zhao, H Cao, S Liu, S He, ... arXiv preprint arXiv:2404.01268, 2024 | 41 | 2024 |
Disparities in dermatology ai: Assessments using diverse clinical images R Daneshjou, K Vodrahalli, W Liang, RA Novoa, M Jenkins, V Rotemberg, ... arXiv preprint arXiv:2111.08006, 2021 | 38 | 2021 |
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation W Liang, J Zou, Z Yu ACL 2020; arXiv preprint arXiv:2005.10716, 2020 | 37 | 2020 |
Opendataval: a unified benchmark for data valuation K Jiang, W Liang, JY Zou, Y Kwon Advances in Neural Information Processing Systems 36, 2023 | 27 | 2023 |
Cu-net: Component unmixing network for textile fiber identification Z Feng, W Liang, D Tao, L Sun, A Zeng, M Song International Journal of Computer Vision 127, 1443-1454, 2019 | 27 | 2019 |
Characterizing the clinical adoption of medical AI devices through US insurance claims K Wu, E Wu, B Theodorou, W Liang, C Mack, L Glass, J Sun, J Zou NEJM AI 1 (1), AIoa2300030, 2023 | 26 | 2023 |
Can large language models provide useful feedback on research papers W Liang, Y Zhang, H Cao, B Wang, D Ding, X Yang, K Vodrahalli, S He, ... A large-scale empirical analysis. In arXiv preprint, 2023 | 26 | 2023 |