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ORCIDXia Ben Hu
Xia (Ben) Hu – Xia Hu 0001
Person information
- affiliation: Rice University, Department of Computer Science, Houston, TX, USA
- affiliation (former): Texas A&M University, Department of Computer Science and Engineering, College Station, TX, USA
- affiliation (PhD): Arizona State University, Department of Computer Science, Tempe, AZ, USA
- affiliation (former): Beihang University, Beijing, China
Other persons with the same name
- Xia Hu — disambiguation page
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2020 – today
- 2024
[j56]Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu:
Shortcut Learning of Large Language Models in Natural Language Understanding. Commun. ACM 67(1): 110-120 (2024)- [j55]Ruixiang Tang
, Yu-Neng Chuang, Xia Hu:
The Science of Detecting LLM-Generated Text. Commun. ACM 67(4): 50-59 (2024) - [j54]Zirui Liu, Qingquan Song, Li Li, Soo-Hyun Choi, Rui Chen, Xia Hu:
PME: pruning-based multi-size embedding for recommender systems. Frontiers Big Data 6 (2024) - [j53]Aokun Chen, Yunpeng Zhao, Yi Zheng, Hui Hu, Xia Hu, Jennifer N. Fishe, William R. Hogan, Elizabeth A. Shenkman, Yi Guo, Jiang Bian:
Exploring the Relation between Contextual Social Determinants of Health and COVID-19 Occurrence and Hospitalization. Informatics 11: 4 (2024) - [j52]Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu:
SPeC: A Soft Prompt-Based Calibration on Performance Variability of Large Language Model in Clinical Notes Summarization. J. Biomed. Informatics 151: 104606 (2024) - [j51]Sirui Ding, Shenghan Zhang, Xia Hu, Na Zou:
Identify and mitigate bias in electronic phenotyping: A comprehensive study from computational perspective. J. Biomed. Informatics 156: 104671 (2024) - [j50]Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Shaochen Zhong, Bing Yin, Xia Ben Hu:
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. ACM Trans. Knowl. Discov. Data 18(6): 160:1-160:32 (2024) - [j49]Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu:
Collaborative Graph Neural Networks for Attributed Network Embedding. IEEE Trans. Knowl. Data Eng. 36(3): 972-986 (2024) - [j48]Tianming Liu, Dajiang Zhu, Fei Wang, Islem Rekik, Xia Ben Hu, Dinggang Shen:
Editorial Special Issue on Explainable and Generalizable Deep Learning for Medical Imaging. IEEE Trans. Neural Networks Learn. Syst. 35(6): 7271-7274 (2024) - [c188]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
Chasing Fairness in Graphs: A GNN Architecture Perspective. AAAI 2024: 21214-21222 - [c187]Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin:
Unraveling the 'Anomaly' in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. ICDE 2024: 981-994 - [c186]Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu:
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. ICLR 2024 - [c185]Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu:
LLM Maybe LongLM: SelfExtend LLM Context Window Without Tuning. ICML 2024 - [c184]Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu:
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache. ICML 2024 - [c183]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
TVE: Learning Meta-attribution for Transferable Vision Explainer. ICML 2024 - [c182]Zhaozhuo Xu, Zirui Liu, Beidi Chen, Shaochen Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava:
Soft Prompt Recovers Compressed LLMs, Transferably. ICML 2024 - [c181]Shaochen Zhong, Duy Le, Zirui Liu, Zhimeng Jiang, Andrew Ye, Jiamu Zhang, Jiayi Yuan, Kaixiong Zhou, Zhaozhuo Xu, Jing Ma, Shuai Xu, Vipin Chaudhary, Xia Hu:
GNNs Also Deserve Editing, and They Need It More Than Once. ICML 2024 - [c180]Ruixiang Tang, Yu-Neng Chuang, Xuanting Cai, Mengnan Du, Xia Hu:
Secure Your Model: An Effective Key Prompt Protection Mechanism for Large Language Models. NAACL-HLT (Findings) 2024: 4061-4073 - [c179]Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu, Xun Chen, Xia Ben Hu:
Learning to Compress Prompt in Natural Language Formats. NAACL-HLT 2024: 7756-7767 - [c178]Huiyuan Chen, Vivian Lai, Hongye Jin, Zhimeng Jiang, Mahashweta Das, Xia Hu:
Towards Mitigating Dimensional Collapse of Representations in Collaborative Filtering. WSDM 2024: 106-115 - [i149]Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Zirui Liu, Chia-Yuan Chang, Huiyuan Chen, Xia Hu:
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning. CoRR abs/2401.01325 (2024) - [i148]Zirui Liu, Qingquan Song, Qiang Charles Xiao, Sathiya Keerthi Selvaraj, Rahul Mazumder, Aman Gupta, Xia Hu:
FFSplit: Split Feed-Forward Network For Optimizing Accuracy-Efficiency Trade-off in Language Model Inference. CoRR abs/2401.04044 (2024) - [i147]Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu:
KIVI: A Tuning-Free Asymmetric 2bit Quantization for KV Cache. CoRR abs/2402.02750 (2024) - [i146]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Ruixiang Tang, Fan Yang, Mengnan Du, Xuanting Cai, Xia Hu:
Large Language Models As Faithful Explainers. CoRR abs/2402.04678 (2024) - [i145]Aokun Chen, Qian Li, Yu Huang, Yongqiu Li, Yu-Neng Chuang, Xia Hu, Serena Guo, Yonghui Wu, Yi Guo, Jiang Bian:
Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data. CoRR abs/2402.15515 (2024) - [i144]Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu, Xun Chen, Xia Hu:
Learning to Compress Prompt in Natural Language Formats. CoRR abs/2402.18700 (2024) - [i143]Hongyi Liu, Zirui Liu, Ruixiang Tang, Jiayi Yuan, Shaochen Zhong, Yu-Neng Chuang, Li Li, Rui Chen, Xia Hu:
LoRA-as-an-Attack! Piercing LLM Safety Under The Share-and-Play Scenario. CoRR abs/2403.00108 (2024) - [i142]Yu-Neng Chuang, Songchen Li, Jiayi Yuan, Guanchu Wang, Kwei-Herng Lai, Leisheng Yu, Sirui Ding, Chia-Yuan Chang, Qiaoyu Tan, Daochen Zha, Xia Hu:
Understanding Different Design Choices in Training Large Time Series Models. CoRR abs/2406.14045 (2024) - [i141]Jiayi Yuan, Hongyi Liu, Shaochen Zhong, Yu-Neng Chuang, Songchen Li, Guanchu Wang, Duy Le, Hongye Jin, Vipin Chaudhary, Zhaozhuo Xu, Zirui Liu, Xia Hu:
KV Cache Compression, But What Must We Give in Return? A Comprehensive Benchmark of Long Context Capable Approaches. CoRR abs/2407.01527 (2024) - [i140]Guanchu Wang, Junhao Ran, Ruixiang Tang, Chia-Yuan Chang, Yu-Neng Chuang, Zirui Liu, Vladimir Braverman, Zhandong Liu, Xia Hu:
Assessing and Enhancing Large Language Models in Rare Disease Question-answering. CoRR abs/2408.08422 (2024) - 2023
- [j47]Zhaoyi Chen, Yuchen Yang, Dazheng Zhang, Jingchuan Guo, Yi Guo, Xia Hu, Yong Chen, Jiang Bian:
Predicting the Risk of Alzheimer's Disease and Related Dementia in Patients with Mild Cognitive Impairment Using a Semi-Competing Risk Approach. Informatics 10(2): 46 (2023) - [j46]Can Li, Sirui Ding, Na Zou, Xia Hu, Xiaoqian Jiang, Kai Zhang:
Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling. J. Biomed. Informatics 143: 104399 (2023) - [j45]Tianlong Chen, Kaixiong Zhou, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang:
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 2769-2781 (2023) - [j44]Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu:
Did You Train on My Dataset? Towards Public Dataset Protection with CleanLabel Backdoor Watermarking. SIGKDD Explor. 25(1): 43-53 (2023) - [j43]Zhimeng Jiang, Kaixiong Zhou, Mi Zhang, Rui Chen, Xia Hu, Soo-Hyun Choi:
Adaptive RiskAware Bidding with Budget Constraint in Display Advertising. SIGKDD Explor. 25(1): 73-82 (2023) - [j42]Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, Xia Hu:
Retiring ΔDP: New Distribution-Level Metrics for Demographic Parity. Trans. Mach. Learn. Res. 2023 (2023) - [j41]Zirui Liu, Kaixiong Zhou, Zhimeng Jiang, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
DSpar: An Embarrassingly Simple Strategy for Efficient GNN training and inference via Degree-based Sparsification. Trans. Mach. Learn. Res. 2023 (2023) - [c177]Qizhang Feng, Jiayi Yuan, Forhan Bin Emdad, Karim Hanna, Xia Hu, Zhe He:
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke. BCB 2023: 26:1-26:6 - [c176]Kwei-Herng Lai, Daochen Zha, Huiyuan Chen, Mangesh Bendre, Yuzhong Chen, Mahashweta Das, Hao Yang, Xia Hu:
Tackling Diverse Minorities in Imbalanced Classification. CIKM 2023: 1178-1187 - [c175]Ruixiang Tang, Hongye Jin, Mengnan Du, Curtis Wigington, Rajiv Jain, Xia Hu:
Exposing Model Theft: A Robust and Transferable Watermark for Thwarting Model Extraction Attacks. CIKM 2023: 4315-4319 - [c174]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Hu:
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CIKM 2023: 5021-5025 - [c173]Mengnan Du, Subhabrata Mukherjee, Yu Cheng, Milad Shokouhi, Xia Hu, Ahmed Hassan Awadallah:
Robustness Challenges in Model Distillation and Pruning for Natural Language Understanding. EACL 2023: 1758-1770 - [c172]Yezi Liu, Qinggang Zhang, Mengnan Du, Xiao Huang, Xia Hu:
Error Detection on Knowledge Graphs with Triple Embedding. EUSIPCO 2023: 1604-1608 - [c171]Andrew T. Lian, Alfredo Costilla-Reyes, Xia Hu:
CAPTAIN: An AI-Based Chatbot for Cyberbullying Prevention and Intervention. HCI (41) 2023: 98-107 - [c170]Qiaoyu Tan, Daochen Zha, Ninghao Liu, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu:
Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation. ICDM 2023: 1343-1348 - [c169]Shenghan Zhang, Haoxuan Li, Ruixiang Tang, Sirui Ding, Laila Rasmy, Degui Zhi, Na Zou, Xia Hu:
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. ICHI 2023: 268-275 - [c168]Yu-Neng Chuang, Guanchu Wang, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
CoRTX: Contrastive Framework for Real-time Explanation. ICLR 2023 - [c167]Xiaotian Han, Tong Zhao, Yozen Liu, Xia Hu, Neil Shah:
MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization. ICLR 2023 - [c166]Zirui Liu, Shengyuan Chen, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu:
RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations. ICML 2023: 21951-21968 - [c165]Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Ben Hu:
DIVISION: Memory Efficient Training via Dual Activation Precision. ICML 2023: 36036-36057 - [c164]Huiyuan Chen, Kaixiong Zhou, Zhimeng Jiang, Chin-Chia Michael Yeh, Xiaoting Li, Menghai Pan, Yan Zheng, Xia Hu, Hao Yang:
Probabilistic Masked Attention Networks for Explainable Sequential Recommendation. IJCAI 2023: 2068-2076 - [c163]Yue Xu, Hao Chen, Zefan Wang, Jianwen Yin, Qijie Shen, Dimin Wang, Feiran Huang, Lixiang Lai, Tao Zhuang, Junfeng Ge, Xia Hu:
Multi-factor Sequential Re-ranking with Perception-Aware Diversification. KDD 2023: 5327-5337 - [c162]Daochen Zha, Kwei-Herng Lai, Fan Yang, Na Zou, Huiji Gao, Xia Hu:
Data-centric AI: Techniques and Future Perspectives. KDD 2023: 5839-5840 - [c161]Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu:
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. MLSys 2023 - [c160]Qizhang Feng, Zhimeng Stephen Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu:
Fair Graph Distillation. NeurIPS 2023 - [c159]Zhimeng Stephen Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu:
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach. NeurIPS 2023 - [c158]Zirui Liu, Guanchu Wang, Shaochen (Henry) Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang (Ryan) Tang, Zhimeng Stephen Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Hu:
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. NeurIPS 2023 - [c157]Ruixiang (Ryan) Tang, Jiayi Yuan, Yiming Li, Zirui Liu, Rui Chen, Xia Hu:
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots. NeurIPS 2023 - [c156]Shaochen (Henry) Zhong, Zaichuan You, Jiamu Zhang, Sebastian Zhao, Zachary LeClaire, Zirui Liu, Daochen Zha, Vipin Chaudhary, Shuai Xu, Xia Hu:
One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning. NeurIPS 2023 - [c155]Ruixiang Tang, Mengnan Du, Xia Hu:
Deep Serial Number: Computational Watermark for DNN Intellectual Property Protection. ECML/PKDD (6) 2023: 157-173 - [c154]Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu:
Mitigating Algorithmic Bias with Limited Annotations. ECML/PKDD (2) 2023: 241-258 - [c153]Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang:
Hessian-aware Quantized Node Embeddings for Recommendation. RecSys 2023: 757-762 - [c152]Kaixiong Zhou, Soo-Hyun Choi, Zirui Liu, Ninghao Liu, Fan Yang, Rui Chen, Li Li, Xia Hu:
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. SDM 2023: 55-63 - [c151]Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu:
Context-aware Domain Adaptation for Time Series Anomaly Detection. SDM 2023: 676-684 - [c150]Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Xia Hu:
Data-centric AI: Perspectives and Challenges. SDM 2023: 945-948 - [c149]Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection. WSDM 2023: 625-633 - [c148]Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu:
S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking. WSDM 2023: 787-795 - [i139]Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Xia Hu:
Data-centric AI: Perspectives and Challenges. CoRR abs/2301.04819 (2023) - [i138]Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, Xia Hu:
Retiring $Δ$DP: New Distribution-Level Metrics for Demographic Parity. CoRR abs/2301.13443 (2023) - [i137]Yu-Neng Chuang, Guanchu Wang, Fan Yang, Zirui Liu, Xuanting Cai, Mengnan Du, Xia Ben Hu:
Efficient XAI Techniques: A Taxonomic Survey. CoRR abs/2302.03225 (2023) - [i136]Sirui Ding, Ruixiang Tang, Daochen Zha, Na Zou, Kai Zhang, Xiaoqian Jiang, Xia Hu:
Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning. CoRR abs/2302.09400 (2023) - [i135]Diego Martinez, Daochen Zha, Qiaoyu Tan, Xia Hu:
Towards Personalized Preprocessing Pipeline Search. CoRR abs/2302.14329 (2023) - [i134]Yu-Neng Chuang, Guanchu Wang, Fan Yang, Quan Zhou, Pushkar Tripathi, Xuanting Cai, Xia Ben Hu:
CoRTX: Contrastive Framework for Real-time Explanation. CoRR abs/2303.02794 (2023) - [i133]Zhimeng Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Na Zou, Xia Ben Hu:
Weight Perturbation Can Help Fairness under Distribution Shift. CoRR abs/2303.03300 (2023) - [i132]Ruixiang Tang, Xiaotian Han, Xiaoqian Jiang, Xia Hu:
Does Synthetic Data Generation of LLMs Help Clinical Text Mining? CoRR abs/2303.04360 (2023) - [i131]Ruixiang Tang, Yu-Neng Chuang, Xia Hu:
The Science of Detecting LLM-Generated Texts. CoRR abs/2303.07205 (2023) - [i130]Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Zhimeng Jiang, Shaochen Zhong, Xia Hu:
Data-centric Artificial Intelligence: A Survey. CoRR abs/2303.10158 (2023) - [i129]Shenghan Zhang, Haoxuan Li, Ruixiang Tang, Sirui Ding, Laila Rasmy, Degui Zhi, Na Zou, Xia Hu:
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. CoRR abs/2303.10794 (2023) - [i128]Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu:
Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Watermarking. CoRR abs/2303.11470 (2023) - [i127]Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, Xia Hu:
SPeC: A Soft Prompt-Based Calibration on Mitigating Performance Variability in Clinical Notes Summarization. CoRR abs/2303.13035 (2023) - [i126]Chia-Yuan Chang, Jiayi Yuan, Sirui Ding, Qiaoyu Tan, Kai Zhang, Xiaoqian Jiang, Xia Hu, Na Zou:
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint. CoRR abs/2303.13790 (2023) - [i125]Sirui Ding, Qiaoyu Tan, Chia-Yuan Chang, Na Zou, Kai Zhang, Nathan R. Hoot, Xiaoqian Jiang, Xia Hu:
Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant. CoRR abs/2304.00012 (2023) - [i124]Kwei-Herng Lai, Lan Wang, Huiyuan Chen, Kaixiong Zhou, Fei Wang, Hao Yang, Xia Hu:
Context-aware Domain Adaptation for Time Series Anomaly Detection. CoRR abs/2304.07453 (2023) - [i123]Guanchu Wang, Ninghao Liu, Daochen Zha, Xia Ben Hu:
Interactive System-wise Anomaly Detection. CoRR abs/2304.10704 (2023) - [i122]Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, Xia Hu:
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond. CoRR abs/2304.13712 (2023) - [i121]Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu:
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. CoRR abs/2305.01868 (2023) - [i120]Zhaozhuo Xu, Zirui Liu, Beidi Chen, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava:
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt. CoRR abs/2305.11186 (2023) - [i119]Yue Xu, Hao Chen, Zefan Wang, Jianwen Yin, Qijie Shen, Dimin Wang, Feiran Huang, Lixiang Lai, Tao Zhuang, Junfeng Ge, Xia Hu:
Multi-factor Sequential Re-ranking with Perception-Aware Diversification. CoRR abs/2305.12420 (2023) - [i118]Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu:
DEGREE: Decomposition Based Explanation For Graph Neural Networks. CoRR abs/2305.12895 (2023) - [i117]Zirui Liu, Guanchu Wang, Shaochen Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang Tang, Zhimeng Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Ben Hu:
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model. CoRR abs/2305.15265 (2023) - [i116]Zirui Liu, Zhimeng Jiang, Shaochen Zhong, Kaixiong Zhou, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu:
Editable Graph Neural Network for Node Classifications. CoRR abs/2305.15529 (2023) - [i115]Yao Rong, Guanchu Wang, Qizhang Feng, Ninghao Liu, Zirui Liu, Enkelejda Kasneci, Xia Ben Hu:
Efficient GNN Explanation via Learning Removal-based Attribution. CoRR abs/2306.05760 (2023) - [i114]Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu:
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. CoRR abs/2306.09468 (2023) - [i113]Chia-Yuan Chang, Yu-Neng Chuang, Kwei-Herng Lai, Xiaotian Han, Xia Hu, Na Zou:
Towards Assumption-free Bias Mitigation. CoRR abs/2307.04105 (2023) - [i112]Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu:
Collaborative Graph Neural Networks for Attributed Network Embedding. CoRR abs/2307.11981 (2023) - [i111]Qizhang Feng, Jiayi Yuan, Forhan Bin Emdad, Karim Hanna, Xia Hu, Zhe He:
Can Attention Be Used to Explain EHR-Based Mortality Prediction Tasks: A Case Study on Hemorrhagic Stroke. CoRR abs/2308.05110 (2023) - [i110]Kwei-Herng Lai, Daochen Zha, Huiyuan Chen, Mangesh Bendre, Yuzhong Chen, Mahashweta Das, Hao Yang, Xia Hu:
Tackling Diverse Minorities in Imbalanced Classification. CoRR abs/2308.14838 (2023) - [i109]Huiyuan Chen, Kaixiong Zhou, Kwei-Herng Lai, Chin-Chia Michael Yeh, Yan Zheng, Xia Hu, Hao Yang:
Hessian-aware Quantized Node Embeddings for Recommendation. CoRR abs/2309.01032 (2023) - [i108]Yu-Neng Chuang, Guanchu Wang, Chia-Yuan Chang, Kwei-Herng Lai, Daochen Zha, Ruixiang Tang, Fan Yang, Alfredo Costilla-Reyes, Kaixiong Zhou, Xiaoqian Jiang, Xia Ben Hu:
DiscoverPath: A Knowledge Refinement and Retrieval System for Interdisciplinarity on Biomedical Research. CoRR abs/2309.01808 (2023) - [i107]Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu:
On the Equivalence of Graph Convolution and Mixup. CoRR abs/2310.00183 (2023) - [i106]Hongye Jin, Xiaotian Han, Jingfeng Yang, Zhimeng Jiang, Chia-Yuan Chang, Xia Hu:
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length. CoRR abs/2310.00576 (2023) - [i105]Ruixiang Tang, Jiayi Yuan, Yiming Li, Zirui Liu, Rui Chen, Xia Hu:
Setting the Trap: Capturing and Defeating Backdoors in Pretrained Language Models through Honeypots. CoRR abs/2310.18633 (2023) - [i104]Yuting Sun, Guansong Pang, Guanhua Ye, Tong Chen, Xia Hu, Hongzhi Yin:
Unraveling the "Anomaly" in Time Series Anomaly Detection: A Self-supervised Tri-domain Solution. CoRR abs/2311.11235 (2023) - [i103]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
Chasing Fairness in Graphs: A GNN Architecture Perspective. CoRR abs/2312.12369 (2023) - [i102]Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu:
LETA: Learning Transferable Attribution for Generic Vision Explainer. CoRR abs/2312.15359 (2023) - [i101]