Xuanqing Liu - RankMe

39 papers A* 10Journal 24Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks. CoRR Xiangyi Li, Wenbo Chen, Yimin Liu, Shenghan Zheng, Xiaokun Chen, Yifeng He, Yubo Li, Bingran You, Haotian Shen, Jiankai Sun, Shuyi Wang, Qunhong Zeng, Di Wang, Xuandong Zhao, Yuanli Wang, Roey Ben Chaim, Zonglin Di, Yipeng Gao, Junwei He, Yizhuo He, Liqiang Jing, Luyang Kong, Xin Lan, Jiachen Li, Songlin Li, Yijiang Li, Yueqian Lin, Xinyi Liu, Xuanqing Liu, Haoran Lyu, Ze Ma, Bowei Wang, Runhui Wang, Tianfu Wang, Wengao Ye, Yue Zhang, Hanwen Xing, Yiqi Xue, Steven Dillmann, Han-Chung Lee
2025	J	`jnl`	Declarative Data Pipeline for Large Scale ML Services. CoRR Yunzhao Yang, Runhui Wang, Xuanqing Liu, Adit Krishnan, Yefan Tao, Yuqian Deng, Kuangyou Yao, Peiyuan Sun, Henrik Johnson, Aditi Sinha, Davor Golac, Gerald Friedland, Usman Shakeel, Daryl Cooke, Joe Sullivan, Chris Kong
2025	—	`conf`	Learning LLM Preference over Intra-Dialogue Pairs: A Framework for Utterance-level Understandings. NAACL (Industry Track) Xuanqing Liu, Luyang Kong, Wei Niu, Afshin Khashei, Belinda Zeng, Steve Johnson, Jon Jay, Davor Golac, Matt Pope
2025	J	`jnl`	Learning LLM Preference over Intra-Dialogue Pairs: A Framework for Utterance-level Understandings. CoRR Xuanqing Liu, Luyang Kong, Wei Niu, Afshin Khashei, Belinda Zeng, Steve Johnson, Jon Jay, Davor Golac, Matt Pope
2025	J	`jnl`	Stochastic Optimization for Nonconvex Problem With Inexact Hessian Matrix, Gradient, and Function. IEEE Trans. Neural Networks Learn. Syst. Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
2024	—	`conf`	BPID: A Benchmark for Personal Identity Deduplication. EMNLP (Industry Track) Runhui Wang, Yefan Tao, Adit Krishnan, Luyang Kong, Xuanqing Liu, Yuqian Deng, Yunzhao Yang, Henrik Johnson, Andrew Borthwick, Shobhit Gupta, Aditi Gundlapalli, Davor Golac
2024	A*	`conf`	GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security. KDD Xuanqing Liu, Runhui Wang, Yang Song, Luyang Kong
2024	J	`jnl`	GRAM: Generative Retrieval Augmented Matching of Data Schemas in the Context of Data Security. CoRR Xuanqing Liu, Luyang Kong, Runhui Wang, Patrick Song, Austin Nevins, Henrik Johnson, Nimish Amlathe, Davor Golac
2023	J	`jnl`	Stochastic Optimization for Non-convex Problem with Inexact Hessian Matrix, Gradient, and Function. CoRR Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
2021	—	`—`	Building Trustworthy Machine Learning Models. Xuanqing Liu
2021	A*	`conf`	Evaluations and Methods for Explanation through Robustness Analysis. ICLR Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Kumar Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
2021	A*	`conf`	Label Disentanglement in Partition-based Extreme Multilabel Classification. NeurIPS Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2021	J	`jnl`	Label Disentanglement in Partition-based Extreme Multilabel Classification. CoRR Xuanqing Liu, Wei-Cheng Chang, Hsiang-Fu Yu, Cho-Jui Hsieh, Inderjit S. Dhillon
2020	J	`jnl`	Evaluations and Methods for Explanation through Robustness Analysis. CoRR Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
2020	J	`jnl`	Gradient Boosting Neural Networks: GrowNet. CoRR Sarkhan Badirli, Xuanqing Liu, Zhengming Xing, Avradeep Bhowmik, Sathiya S. Keerthi
2020	A*	`conf`	How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. CVPR Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
2020	J	`jnl`	How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers. CoRR Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You, Si Si, Cho-Jui Hsieh
2020	J	`jnl`	Improving the Speed and Quality of GAN by Adversarial Training. CoRR Jiachen Zhong, Xuanqing Liu, Cho-Jui Hsieh
2020	A*	`conf`	Learning to Encode Position for Transformer with Continuous Dynamical Model. ICML Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	J	`jnl`	Learning to Encode Position for Transformer with Continuous Dynamical Model. CoRR Xuanqing Liu, Hsiang-Fu Yu, Inderjit S. Dhillon, Cho-Jui Hsieh
2020	A*	`conf`	Provably Robust Metric Learning. NeurIPS Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
2020	J	`jnl`	Provably Robust Metric Learning. CoRR Lu Wang, Xuanqing Liu, Jinfeng Yi, Yuan Jiang, Cho-Jui Hsieh
2019	A*	`conf`	A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. NeurIPS Xuanqing Liu, Si Si, Jerry Zhu, Yang Li, Cho-Jui Hsieh
2019	J	`jnl`	A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. CoRR Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, Cho-Jui Hsieh
2019	—	`conf`	Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. ICLR (Poster) Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
2019	A*	`conf`	Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. KDD Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh
2019	J	`jnl`	Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. CoRR Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh
2019	J	`jnl`	Evaluating the Robustness of Nearest Neighbor Classifiers: A Primal-Dual Perspective. CoRR Lu Wang, Xuanqing Liu, Jinfeng Yi, Zhi-Hua Zhou, Cho-Jui Hsieh
2019	J	`jnl`	GraphDefense: Towards Robust Graph Convolutional Networks. CoRR Xiaoyun Wang, Xuanqing Liu, Cho-Jui Hsieh
2019	J	`jnl`	Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise. CoRR Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh
2019	A*	`conf`	Rob-GAN: Generator, Discriminator, and Adversarial Attacker. CVPR Xuanqing Liu, Cho-Jui Hsieh
2018	J	`jnl`	Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network. CoRR Xuanqing Liu, Yao Li, Chongruo Wu, Cho-Jui Hsieh
2018	A*	`conf`	Fast Variance Reduction Method with Stochastic Batch Size. ICML Xuanqing Liu, Cho-Jui Hsieh
2018	J	`jnl`	Fast Variance Reduction Method with Stochastic Batch Size. CoRR Xuanqing Liu, Cho-Jui Hsieh
2018	J	`jnl`	From Adversarial Training to Generative Adversarial Networks. CoRR Xuanqing Liu, Cho-Jui Hsieh
2018	J	`jnl`	Stochastic Second-order Methods for Non-convex Optimization with Inexact Hessian and Gradient. CoRR Liu Liu, Xuanqing Liu, Cho-Jui Hsieh, Dacheng Tao
2018	—	`conf`	Towards Robust Neural Networks via Random Self-ensemble. ECCV (7) Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh
2017	J	`jnl`	An inexact subsampled proximal Newton-type method for large-scale machine learning. CoRR Xuanqing Liu, Cho-Jui Hsieh, Jason D. Lee, Yuekai Sun
2017	J	`jnl`	Towards Robust Neural Networks via Random Self-ensemble. CoRR Xuanqing Liu, Minhao Cheng, Huan Zhang, Cho-Jui Hsieh