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Weixin Liang
Weixin Liang
Stanford Univerisity
Verified email at stanford.edu
Title
Cited by
Cited by
Year
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
3082022
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
3022022
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
2822023
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
2032022
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
1812022
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
792019
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
712024
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
712022
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
672024
Alice: Active learning with contrastive natural language explanations
W Liang, J Zou, Z Yu
EMNLP 2020; arXiv preprint arXiv:2009.10259, 2020
492020
Dawson: A domain adaptive few shot generation framework
W Liang, Z Liu, C Liu
arXiv preprint arXiv:2001.00576, 2020
482020
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
442019
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
422021
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
412024
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
382021
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
372020
Opendataval: a unified benchmark for data valuation
K Jiang, W Liang, JY Zou, Y Kwon
Advances in Neural Information Processing Systems 36, 2023
272023
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
272019
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
262023
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
262023
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