Huaxiu Yao

ORCID

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 116

Top Venues

Publications

Zhiyuan Wang, Jinhao Duan, Chenxi Yuan, Qingyu Chen, Tianlong Chen, Huaxiu Yao, Yue Zhang, Ren Wang, Kaidi Xu, Xiaoshuang Shi
Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond. CoRR (2024)
Yiyang Zhou, Zhiyuan Fan, Dongjie Cheng, Sihan Yang, Zhaorun Chen, Chenhang Cui, Xiyao Wang, Yun Li, Linjun Zhang, Huaxiu Yao
Calibrated Self-Rewarding Vision Language Models. CoRR (2024)
Wenhao Zheng, Dongsheng Peng, Hongxia Xu, Hongtu Zhu, Tianfan Fu, Huaxiu Yao
Multimodal Clinical Trial Outcome Prediction with Large Language Models. CoRR (2024)
Qichuan Yin, Junzhou Huang, Huaxiu Yao, Linjun Zhang
Distribution-Free Fair Federated Learning with Small Samples. CoRR (2024)
Zhen-Yu Zhang, Siwei Han, Huaxiu Yao, Gang Niu, Masashi Sugiyama
Generating Chain-of-Thoughts with a Direct Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought. CoRR (2024)
Viet Duong, Qiong Wu, Zhengyi Zhou, Hongjue Zhao, Chenxiang Luo, Eric Zavesky, Huaxiu Yao, Huajie Shao
CAT: Interpretable Concept-based Taylor Additive Models. KDD (2024)
Haoran Li, Junqi Liu, Zexian Wang, Shiyuan Luo, Xiaowei Jia, Huaxiu Yao
LITE: Modeling Environmental Ecosystems with Multimodal Large Language Models. CoRR (2024)
Xiyao Wang, Jiuhai Chen, Zhaoyang Wang, Yuhang Zhou, Yiyang Zhou, Huaxiu Yao, Tianyi Zhou, Tom Goldstein, Parminder Bhatia, Furong Huang, Cao Xiao
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement. CoRR (2024)
Taiming Lu, Lingfeng Shen, Xinyu Yang, Weiting Tan, Beidi Chen, Huaxiu Yao
It Takes Two: On the Seamlessness between Reward and Policy Model in RLHF. CoRR (2024)
Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Fuxiao Liu, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, Furong Huang
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. ACL (1) (2024)
Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn
Conservative Prediction via Data-Driven Confidence Minimization. Trans. Mach. Learn. Res. 2024 (2024)
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chao Zhang, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao
TrustLLM: Trustworthiness in Large Language Models. CoRR (2024)
Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu, Ruiqi Zhang, Xiang Li, Bhiksha Raj, Huaxiu Yao
AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition. CoRR (2024)
Zhaorun Chen, Yichao Du, Zichen Wen, Yiyang Zhou, Chenhang Cui, Zhenzhen Weng, Haoqin Tu, Chaoqi Wang, Zhengwei Tong, Qinglan Huang, Canyu Chen, Qinghao Ye, Zhihong Zhu, Yuqing Zhang, Jiawei Zhou, Zhuokai Zhao, Rafael Rafailov, Chelsea Finn, Huaxiu Yao
MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation? CoRR (2024)
Canyu Chen, Baixiang Huang, Zekun Li, Zhaorun Chen, Shiyang Lai, Xiongxiao Xu, Jia-Chen Gu, Jindong Gu, Huaxiu Yao, Chaowei Xiao, Xifeng Yan, William Yang Wang, Philip Torr, Dawn Song, Kai Shu
Can Editing LLMs Inject Harm? CoRR (2024)
Huaxiu Yao
Towards Reliable Learning in the Wild: Generalization and Adaptation. AAAI (2024)
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. ICLR (2024)
Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn
Fine-Tuning Language Models for Factuality. ICLR (2024)
Yiyang Zhou, Chenhang Cui, Rafael Rafailov, Chelsea Finn, Huaxiu Yao
Aligning Modalities in Vision Large Language Models via Preference Fine-tuning. CoRR (2024)
Zongbo Han, Yifeng Yang, Changqing Zhang, Linjun Zhang, Joey Tianyi Zhou, Qinghua Hu, Huaxiu Yao
Selective Learning: Towards Robust Calibration with Dynamic Regularization. CoRR (2024)
Viet Duong, Qiong Wu, Zhengyi Zhou, Hongjue Zhao, Chenxiang Luo, Eric Zavesky, Huaxiu Yao, Huajie Shao
CAT: Interpretable Concept-based Taylor Additive Models. CoRR (2024)
Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn
Improving Domain Generalization with Domain Relations. ICLR (2024)
Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models. CoRR (2024)
Zhaorun Chen, Zhuokai Zhao, Hongyin Luo, Huaxiu Yao, Bo Li, Jiawei Zhou
HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding. CoRR (2024)
Taixi Lu, Haoyu Wang, Huajie Shao, Jing Gao, Huaxiu Yao
: Confidence Calibration Model Cascade for Inference-Efficient Cross-Lingual Natural Language Understanding. CoRR (2024)
Peng Xia, Ming Hu, Feilong Tang, Wenxue Li, Wenhao Zheng, Lie Ju, Peibo Duan, Huaxiu Yao, Zongyuan Ge
Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations. CoRR (2024)
Peng Xia, Kangyu Zhu, Haoran Li, Hongtu Zhu, Yun Li, Gang Li, Linjun Zhang, Huaxiu Yao
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models. CoRR (2024)
Xiyao Wang, Yuhang Zhou, Xiaoyu Liu, Hongjin Lu, Yuancheng Xu, Feihong He, Jaehong Yoon, Taixi Lu, Gedas Bertasius, Mohit Bansal, Huaxiu Yao, Furong Huang
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences. CoRR (2024)
Zhaorun Chen, Zhuokai Zhao, Zhihong Zhu, Ruiqi Zhang, Xiang Li, Bhiksha Raj, Huaxiu Yao
AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition. NAACL-HLT (2024)
Zhongwei Wan, Che Liu, Xin Wang, Chaofan Tao, Hui Shen, Zhenwu Peng, Jie Fu, Rossella Arcucci, Huaxiu Yao, Mi Zhang
Electrocardiogram Instruction Tuning for Report Generation. CoRR (2024)
Shiyuan Luo, Juntong Ni, Shengyu Chen, Runlong Yu, Yiqun Xie, Licheng Liu, Zhenong Jin, Huaxiu Yao, Xiaowei Jia
FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems. CoRR (2023)
Haoyu Wang, Yaqing Wang, Huaxiu Yao, Jing Gao
Macedon: Minimizing Representation Coding Rate Reduction for Cross-Lingual Natural Language Understanding. EMNLP (Findings) (2023)
Haoqin Tu, Chenhang Cui, Zijun Wang, Yiyang Zhou, Bingchen Zhao, Junlin Han, Wangchunshu Zhou, Huaxiu Yao, Cihang Xie
How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs. CoRR (2023)
Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou
Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks. CoRR (2023)
Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. ICLR (2023)
Yoonho Lee, Huaxiu Yao, Chelsea Finn
Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement. ICLR (2023)
Zhenbang Wu, Huaxiu Yao, David M. Liebovitz, Jimeng Sun
An Iterative Self-Learning Framework for Medical Domain Generalization. NeurIPS (2023)
Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. CoRR (2023)
Yunzhe Qi, Yikun Ban, Tianxin Wei, Jiaru Zou, Huaxiu Yao, Jingrui He
Meta-Learning with Neural Bandit Scheduler. NeurIPS (2023)
Jianguo Huang, Huajun Xi, Linjun Zhang, Huaxiu Yao, Yue Qiu, Hongxin Wei
Conformal Prediction for Deep Classifier via Label Ranking. CoRR (2023)
Chenhang Cui, Yiyang Zhou, Xinyu Yang, Shirley Wu, Linjun Zhang, James Zou, Huaxiu Yao
Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges. CoRR (2023)
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023)
Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn
Conservative Prediction via Data-Driven Confidence Minimization. CoRR (2023)
Xiaohui Zhang, Jaehong Yoon, Mohit Bansal, Huaxiu Yao
Multimodal Representation Learning by Alternating Unimodal Adaptation. CoRR (2023)
Katherine Tian, Eric Mitchell, Huaxiu Yao, Christopher D. Manning, Chelsea Finn
Fine-tuning Language Models for Factuality. CoRR (2023)
Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn
Leveraging Domain Relations for Domain Generalization. CoRR (2023)
Xinyu Yang, Huaxiu Yao, Allan Zhou, Chelsea Finn
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations. Trans. Mach. Learn. Res. 2023 (2023)
Yiyang Zhou, Chenhang Cui, Jaehong Yoon, Linjun Zhang, Zhun Deng, Chelsea Finn, Mohit Bansal, Huaxiu Yao
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models. CoRR (2023)
Haoqiang Kang, Juntong Ni, Huaxiu Yao
Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification. CoRR (2023)
Xinzhe Zuo, Zixiang Chen, Huaxiu Yao, Yuan Cao, Quanquan Gu
Understanding Train-Validation Split in Meta-Learning with Neural Networks. ICLR (2023)
Katherine Tian, Eric Mitchell, Allan Zhou, Archit Sharma, Rafael Rafailov, Huaxiu Yao, Chelsea Finn, Christopher D. Manning
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. EMNLP (2023)
Zhenbang Wu, Huaxiu Yao, Zhe Su, David M. Liebovitz, Lucas M. Glass, James Zou, Chelsea Finn, Jimeng Sun
Knowledge-Driven New Drug Recommendation. CoRR (2022)
Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. NeurIPS (2022)
Yoonho Lee, Huaxiu Yao, Chelsea Finn
Diversify and Disambiguate: Learning From Underspecified Data. CoRR (2022)
Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. CoRR (2022)
Huaxiu Yao, Xinyu Yang, Allan Zhou, Chelsea Finn
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations. CoRR (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)
Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer. 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)
Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. CoRR (2022)
Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu
GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy. NeurIPS (2022)
Huaxiu Yao, Linjun Zhang, Chelsea Finn
Meta-Learning with Fewer Tasks through Task Interpolation. ICLR (2022)
Bin Lu, Xiaoying Gan, Weinan Zhang, Huaxiu Yao, Luoyi Fu, Xinbing Wang
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer. KDD (2022)
Huaxiu Yao, Yiping Wang, Linjun Zhang, James Zou, Chelsea Finn
C-Mixup: Improving Generalization in Regression. CoRR (2022)
Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation. ACL (1) (2022)
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda
Holistic Evaluation of Language Models. CoRR (2022)
Yingxiu Zhao, Zhiliang Tian, Huaxiu Yao, Yinhe Zheng, Dongkyu Lee, Yiping Song, Jian Sun, Nevin L. Zhang
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation. CoRR (2022)
Huaxiu Yao, Yiping Wang, Linjun Zhang, James Y. Zou, Chelsea Finn
C-Mixup: Improving Generalization in Regression. NeurIPS (2022)
Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing
Knowledge-Aware Meta-learning for Low-Resource Text Classification. CoRR (2021)
Jiatu Shi, Huaxiu Yao, Xian Wu, Tong Li, Zedong Lin, Tengfei Wang, Binqiang Zhao
Relation-aware Meta-learning for E-commerce Market Segment Demand Prediction with Limited Records. WSDM (2021)
Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn
Meta-learning with an Adaptive Task Scheduler. CoRR (2021)
Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat, Eric P. Xing
Knowledge-Aware Meta-learning for Low-Resource Text Classification. EMNLP (1) (2021)
Porter Jenkins, Ahmad Farag, J. Stockton Jenkins, Huaxiu Yao, Suhang Wang, Zhenhui Li
Neural Utility Functions. AAAI (2021)
Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Li
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery. NeurIPS (2021)
Yanwei Yu, Xianfeng Tang, Huaxiu Yao, Xiuwen Yi, Zhenhui Li
Citywide Traffic Volume Inference with Surveillance Camera Records. IEEE Trans. Big Data 7 (6) (2021)
Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn
Meta-learning with an Adaptive Task Scheduler. NeurIPS (2021)
Huaxiu Yao, Linjun Zhang, Chelsea Finn
Meta-Learning with Fewer Tasks through Task Interpolation. CoRR (2021)
Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla
Inductive Contextual Relation Learning for Personalization. ACM Trans. Inf. Syst. 39 (3) (2021)
Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li
Improving Generalization in Meta-learning via Task Augmentation. ICML (2021)
Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong
Online Structured Meta-learning. NeurIPS (2020)
Huaxiu Yao, Yingbo Zhou, Mehrdad Mahdavi, Zhenhui Li, Richard Socher, Caiming Xiong
Online Structured Meta-learning. CoRR (2020)
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. AAAI (2020)
Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li
Automated Relational Meta-learning. CoRR (2020)
Jiatu Shi, Huaxiu Yao, Xian Wu, Tong Li, Zedong Lin, Tengfei Wang, Binqiang Zhao, Zhenhui Li
Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records. CoRR (2020)
Huaxiu Yao, Xian Wu, Zhiqiang Tao, Yaliang Li, Bolin Ding, Ruirui Li, Zhenhui Li
Automated Relational Meta-learning. ICLR (2020)
Xinshi Zang, Huaxiu Yao, Guanjie Zheng, Nan Xu, Kai Xu, Zhenhui Li
MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control. AAAI (2020)
Xianfeng Tang, Yandong Li, Yiwei Sun, Huaxiu Yao, Prasenjit Mitra, Suhang Wang
Transferring Robustness for Graph Neural Network Against Poisoning Attacks. WSDM (2020)
Zhenhui Li, Huaxiu Yao, Fenglong Ma
Learning with Small Data. WSDM (2020)
Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla
Few-Shot Knowledge Graph Completion. AAAI (2020)
Huaxiu Yao, Longkai Huang, Ying Wei, Li Tian, Junzhou Huang, Zhenhui Li
Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning. CoRR (2020)
Huaxiu Yao, Xiaowei Jia, Vipin Kumar, Zhenhui Li
Learning with Small Data. KDD (2020)
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang
Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks. CIKM (2020)
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang
Graph Convolutional Networks against Degree-Related Biases. CoRR (2020)
Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li
Graph Few-Shot Learning via Knowledge Transfer. AAAI (2020)
Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li
Hierarchically Structured Meta-learning. CoRR (2019)
Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction. WWW (2019)
Huaxiu Yao, Defu Lian, Yi Cao, Yifan Wu, Tao Zhou
Predicting Academic Performance for College Students: A Campus Behavior Perspective. CoRR (2019)
Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li
Graph Few-shot Learning via Knowledge Transfer. CoRR (2019)
Xianfeng Tang, Boqing Gong, Yanwei Yu, Huaxiu Yao, Yandong Li, Haiyong Xie, Xiaoyu Wang
Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference. CoRR (2019)
Huaxiu Yao, Defu Lian, Yi Cao, Yifan Wu, Tao Zhou
Predicting Academic Performance for College Students: A Campus Behavior Perspective. ACM Trans. Intell. Syst. Technol. 10 (3) (2019)

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Publication Activity (10 Years)

Top Topics

Top Venues

Huaxiu Yao