Weixin Liang

According to our database, Weixin Liang authored at least 30 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews.

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

CoRR, 2024

What's documented in AI? Systematic Analysis of 32K AI Model Cards.

Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani, Eric Wu, Yiqun Chen, Daniel Scott Smith, James Zou

CoRR, 2024

Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on Hugging Face.

Xinyu Yang, Weixin Liang, James Zou

CoRR, 2024

2023

GPT detectors are biased against non-native English writers.

Weixin Liang, Mert Yüksekgönül, Yining Mao, Eric Wu, James Zou

Patterns, July, 2023

Can large language models provide useful feedback on research papers? A large-scale empirical analysis.

Weixin Liang, Yuhui Zhang, Hancheng Cao, Binglu Wang, Daisy Ding, Xinyu Yang, Kailas Vodrahalli, Siyu He, Daniel Scott Smith, Yian Yin, Daniel A. McFarland, James Zou

CoRR, 2023

OpenDataVal: a Unified Benchmark for Data Valuation.

Kevin Fu Jiang, Weixin Liang, James Y. Zou, Yongchan Kwon

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Accuracy on the Curve: On the Nonlinear Correlation of ML Performance Between Data Subpopulations.

Weixin Liang, Yining Mao, Yongchan Kwon, Xinyu Yang, James Zou

Proceedings of the International Conference on Machine Learning, 2023

2022

Author Correction: Advances, challenges and opportunities in creating data for trustworthy AI.

Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou

Nat. Mac. Intell., October, 2022

Systematic analysis of 50 years of Stanford University technology transfer and commercialization.

Weixin Liang, Scott Elrod, Daniel A. McFarland, James Zou

Patterns, 2022

Advances, challenges and opportunities in creating data for trustworthy AI.

Weixin Liang, Girmaw Abebe Tadesse, Daniel E. Ho, Li Fei-Fei, Matei Zaharia, Ce Zhang, James Zou

Nat. Mach. Intell., 2022

SEAL : Interactive Tool for Systematic Error Analysis and Labeling.

Nazneen Rajani, Weixin Liang, Lingjiao Chen, Meg Mitchell, James Zou

CoRR, 2022

Data Budgeting for Machine Learning.

Xinyi Zhao, Weixin Liang, James Zou

CoRR, 2022

GSCLIP : A Framework for Explaining Distribution Shifts in Natural Language.

Zhiying Zhu, Weixin Liang, James Zou

CoRR, 2022

Disparities in Dermatology AI Performance on a Diverse, Curated Clinical Image Set.

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

CoRR, 2022

Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning.

Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, James Y. Zou

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Improving Out-of-Distribution Robustness via Selective Augmentation.

Huaxiu Yao, Yu Wang, Sai Li, Linjun Zhang, Weixin Liang, James Zou, Chelsea Finn

Proceedings of the International Conference on Machine Learning, 2022

MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts.

Weixin Liang, James Zou

Proceedings of the Tenth International Conference on Learning Representations, 2022

SEAL: Interactive Tool for Systematic Error Analysis and Labeling.

Nazneen Rajani, Weixin Liang, Lingjiao Chen, Margaret Mitchell, James Zou

Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Disparities in Dermatology AI: Assessments Using Diverse Clinical Images.

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

CoRR, 2021

GraghVQA: Language-Guided Graph Neural Networks for Graph-based Visual Question Answering.

Weixin Liang, Yanhao Jiang, Zixuan Liu

CoRR, 2021

Neural Group Testing to Accelerate Deep Learning.

Weixin Liang, James Zou

Proceedings of the IEEE International Symposium on Information Theory, 2021

HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations.

Weixin Liang, Kaihui Liang, Zhou Yu

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering.

Weixin Liang, Feiyang Niu, Aishwarya N. Reganti, Govind Thattai, Gökhan Tür

CoRR, 2020

DAWSON: A Domain Adaptive Few Shot Generation Framework.

Weixin Liang, Zixuan Liu, Can Liu

CoRR, 2020

ALICE: Active Learning with Contrastive Natural Language Explanations.

Weixin Liang, James Zou, Zhou Yu

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Beyond User Self-Reported Likert Scale Ratings: A Comparison Model for Automatic Dialog Evaluation.

Weixin Liang, James Zou, Zhou Yu

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

MOSS: End-to-End Dialog System Framework with Modular Supervision.

Weixin Liang, Youzhi Tian, Chengcai Chen, Zhou Yu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

CU-Net: Component Unmixing Network for Textile Fiber Identification.

Zunlei Feng, Weixin Liang, Daocheng Tao, Li Sun, Anxiang Zeng, Mingli Song

Int. J. Comput. Vis., 2019

DeepStore: In-Storage Acceleration for Intelligent Queries.

Vikram Sharma Mailthody, Zaid Qureshi, Weixin Liang, Ziyan Feng, Simon Garcia De Gonzalo, Youjie Li, Hubertus Franke, Jinjun Xiong, Jian Huang, Wen-Mei Hwu

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019

2018

MemCloak: Practical Access Obfuscation for Untrusted Memory.

Weixin Liang, Kai Bu, Ke Li, Jinhong Li, Arya Tavakoli

Proceedings of the 34th Annual Computer Security Applications Conference, 2018