Weixin Liang

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 43

Top Topics

Machine Learning

Stanford University

Top Venues

Publications

Xinyu Yang, Weixin Liang, James Zou
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face. CoRR (2024)
Xinyu Yang, Weixin Liang, James Zou
Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace. ICLR (2024)
Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel A. McFarland, James Y. Zou
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews. CoRR (2024)
Weixin Liang, Yaohui Zhang, Zhengxuan Wu, Haley Lepp, Wenlong Ji, Xuandong Zhao, Hancheng Cao, Sheng Liu, Siyu He, Zhi Huang, Diyi Yang, Christopher Potts, Christopher D. Manning, James Y. Zou
Mapping the Increasing Use of LLMs in Scientific Papers. CoRR (2024)
Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani, Eric Wu, Yiqun Chen, Daniel Scott Smith, James Zou
What's documented in AI? Systematic Analysis of 32K AI Model Cards. CoRR (2024)
Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou
On the nonlinear correlation of ML performance between data subpopulations. CoRR (2023)
Kevin Fu Jiang, Weixin Liang, James Zou, Yongchan Kwon
OpenDataVal: a Unified Benchmark for Data Valuation. CoRR (2023)
Kevin Fu Jiang, Weixin Liang, James Y. Zou, Yongchan Kwon
OpenDataVal: a Unified Benchmark for Data Valuation. NeurIPS (2023)
Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou
GPT detectors are biased against non-native English writers. CoRR (2023)
Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou
Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations. ICML (2023)
Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou
GPT detectors are biased against non-native English writers. Patterns 4 (7) (2023)
Weixin Liang, Yuhui Zhang, Hancheng Cao, Binglu Wang, Daisy Ding, Xinyu Yang, Kailas Vodrahalli, Siyu He, Daniel Smith, Yian Yin, Daniel A. McFarland, James Zou
Can large language models provide useful feedback on research papers? A large-scale empirical analysis. CoRR (2023)
Zhiying Zhu, Weixin Liang, James Zou
GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language. CoRR (2022)
Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Y. Zou
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning. NeurIPS (2022)
Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn
Improving Out-of-Distribution Robustness via Selective Augmentation. CoRR (2022)
Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Zou
Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning. CoRR (2022)
Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn
Improving Out-of-Distribution Robustness via Selective Augmentation. ICML (2022)
Weixin Liang, Scott Elrod, Daniel A. McFarland, James Zou
Systematic analysis of 50 years of Stanford University technology transfer and commercialization. Patterns 3 (9) (2022)
Weixin Liang, Girmaw Abebe Tadesse, Daniel Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou
Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mach. Intell. 4 (8) (2022)
Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou
Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI. Nat. Mac. Intell. 4 (10) (2022)
Nazneen Rajani, Weixin Liang, Lingjiao Chen, Meg Mitchell, James Zou
SEAL : Interactive Tool for Systematic Error Analysis and Labeling. CoRR (2022)
Nazneen Rajani, Weixin Liang, Lingjiao Chen, Margaret Mitchell, James Zou
SEAL: Interactive Tool for Systematic Error Analysis and Labeling. EMNLP (Demos) (2022)
Xinyi Zhao, Weixin Liang, James Zou
Data Budgeting for Machine Learning. CoRR (2022)
Weixin Liang, James Zou
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. CoRR (2022)
Roxana Daneshjou, Kailas Vodrahalli, Roberto A. Novoa, Melissa Jenkins, Weixin Liang, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, Johan A. C. Allerup, Utako Okata-Karigane, James Zou, Albert Chiou
Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set. CoRR (2022)
Weixin Liang, James Zou
MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts. ICLR (2022)
Roxana Daneshjou, Kailas Vodrahalli, Weixin Liang, Roberto A. Novoa, Melissa Jenkins, Veronica Rotemberg, Justin Ko, Susan M. Swetter, Elizabeth E. Bailey, Olivier Gevaert, Pritam Mukherjee, Michelle Phung, Kiana Yekrang, Bradley Fong, Rachna Sahasrabudhe, James Zou, Albert Chiou
Disparities in Dermatology AI: Assessments Using Diverse Clinical Images. CoRR (2021)
Weixin Liang, James Zou
Neural Group Testing to Accelerate Deep Learning. ISIT (2021)
Weixin Liang, Kaihui Liang, Zhou Yu
HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations. CoRR (2021)
Weixin Liang, Kaihui Liang, Zhou Yu
HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations. ACL/IJCNLP (1) (2021)
Weixin Liang, Yanhao Jiang, Zixuan Liu
GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering. CoRR (2021)
Weixin Liang, Feiyang Niu, Aishwarya N. Reganti, Govind Thattai, Gökhan Tür
LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering. CoRR (2020)
Weixin Liang, James Zou, Zhou Yu
ALICE: Active Learning with Contrastive Natural Language Explanations. CoRR (2020)
Weixin Liang, James Zou
Neural Group Testing to Accelerate Deep Learning. CoRR (2020)
Weixin Liang, James Zou, Zhou Yu
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. CoRR (2020)
Weixin Liang, Zixuan Liu, Can Liu
DAWSON: A Domain Adaptive Few Shot Generation Framework. CoRR (2020)
Weixin Liang, James Zou, Zhou Yu
Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation. ACL (2020)
Weixin Liang, Youzhi Tian, Chengcai Chen, Zhou Yu
MOSS: End-to-End Dialog System Framework with Modular Supervision. AAAI (2020)
Weixin Liang, James Zou, Zhou Yu
ALICE: Active Learning with Contrastive Natural Language Explanations. EMNLP (1) (2020)
Zunlei Feng, Weixin Liang, Daocheng Tao, Li Sun, Anxiang Zeng, Mingli Song
CU-Net: Component Unmixing Network for Textile Fiber Identification. Int. J. Comput. Vis. 127 (10) (2019)
Vikram Sharma Mailthody, Zaid Qureshi, Weixin Liang, Ziyan Feng, Simon Garcia De Gonzalo, Youjie Li, Hubertus Franke, Jinjun Xiong, Jian Huang, Wen-Mei Hwu
DeepStore: In-Storage Acceleration for Intelligent Queries. MICRO (2019)
Weixin Liang, Youzhi Tian, Chengcai Chen, Zhou Yu
MOSS: End-to-End Dialog System Framework with Modular Supervision. CoRR (2019)
Weixin Liang, Kai Bu, Ke Li, Jinhong Li, Arya Tavakoli
MemCloak: Practical Access Obfuscation for Untrusted Memory. ACSAC (2018)