Xujiang Zhao - RankMe

79 papers A* 15A 5C 1Misc 2Journal 40Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Class-Domain Incremental Learning on Graphs via Disentangled Knowledge Distillation. WWW Qin Tian, Chen Zhao, Xintao Wu, Dong Li, Minglai Shao, Xujiang Zhao, Wenjun Wang
2026	—	`conf`	Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation. EACL (Findings) Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu, Junxiang Wang, Xiang Zhang, Suhang Wang, Haifeng Chen
2026	—	`conf`	DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router. EACL (Findings) Minghao Guo, Qingcheng Zeng, Xujiang Zhao, Yanchi Liu, Wenchao Yu, Mengnan Du, Haifeng Chen, Wei Cheng
2026	J	`jnl`	Distribution shift, generalization and OOD challenge in offline reinforcement learning: a comprehensive survey. Neural Comput. Appl. Ali Riahi Samani, Xujiang Zhao, Feng Chen
2026	J	`jnl`	Domain Specialization as the Key to Make Large Language Models Disruptive: A Comprehensive Survey. ACM Comput. Surv. Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Dhagash Mehta, Stefano Pasquali, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Jian Pei, Carl Yang, Liang Zhao
2026	A*	`conf`	MARLIN: Multi-Agent Reinforcement Learning for Incremental DAG Discovery. AAAI Dong Li, Zhengzhang Chen, Xujiang Zhao, Linlin Yu, Zhong Chen, Yi He, Haifeng Chen, Chen Zhao
2026	J	`jnl`	MARLIN: Multi-Agent Reinforcement Learning for Incremental DAG Discovery. CoRR Dong Li, Zhengzhang Chen, Xujiang Zhao, Linlin Yu, Zhong Chen, Yi He, Haifeng Chen, Chen Zhao
2026	J	`jnl`	Mind the Gap in Cultural Alignment: Task-Aware Culture Management for Large Language Models. CoRR Binchi Zhang, Xujiang Zhao, Jundong Li, Haifeng Chen, Zhengzhang Chen
2026	—	`conf`	Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement. EACL (Findings) Wangyang Ying, Yanchi Liu, Xujiang Zhao, Wei Cheng, Zhengzhang Chen, Wenchao Yu, Yanjie Fu, Haifeng Chen
2026	J	`jnl`	Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement. CoRR Wangyang Ying, Yanchi Liu, Xujiang Zhao, Wei Cheng, Zhengzhang Chen, Wenchao Yu, Yanjie Fu, Haifeng Chen
2026	A*	`conf`	Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models. AAAI Zhixia He, Chen Zhao, Minglai Shao, Xintao Wu, Xujiang Zhao, Dong Li, Qin Tian, Linlin Yu
2026	J	`jnl`	SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning. CoRR Peng Xia, Jianwen Chen, Hanyang Wang, Jiaqi Liu, Kaide Zeng, Yu Wang, Siwei Han, Yiyang Zhou, Xujiang Zhao, Haifeng Chen, Zeyu Zheng, Cihang Xie, Huaxiu Yao
2025	—	`conf`	4th Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM). KDD (2) Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Hua Wei, Haifeng Chen
2025	A	`conf`	Correlation-aware Online Change Point Detection. CIKM Chengyuan Deng, Zhengzhang Chen, Xujiang Zhao, Haoyu Wang, Junxiang Wang, Jie Gao, Haifeng Chen
2025	J	`jnl`	DeepSieve: Information Sieving via LLM-as-a-Knowledge-Router. CoRR Minghao Guo, Qingcheng Zeng, Xujiang Zhao, Yanchi Liu, Wenchao Yu, Mengnan Du, Haifeng Chen, Wei Cheng
2025	A	`conf`	Evidence-Based Out-of-Distribution Detection on Multi-Label Graphs. SDM Ruomeng Ding, Xujiang Zhao, Chen Zhao, Minglai Shao, Zhengzhang Chen, Haifeng Chen
2025	J	`jnl`	Face4FairShifts: A Large Image Benchmark for Fairness and Robust Learning across Visual Domains. CoRR Yumeng Lin, Dong Li, Xintao Wu, Minglai Shao, Xujiang Zhao, Zhong Chen, Chen Zhao
2025	J	`jnl`	Human Texts Are Outliers: Detecting LLM-generated Texts via Out-of-distribution Detection. CoRR Cong Zeng, Shengkun Tang, Yuanzhou Chen, Zhiqiang Shen, Wenchao Yu, Xujiang Zhao, Haifeng Chen, Wei Cheng, Zhiqiang Xu
2025	—	`conf`	MixLLM: Dynamic Routing in Mixed Large Language Models. NAACL (Long Papers) Xinyuan Wang, Yanchi Liu, Wei Cheng, Xujiang Zhao, Zhengzhang Chen, Wenchao Yu, Yanjie Fu, Haifeng Chen
2025	J	`jnl`	MixLLM: Dynamic Routing in Mixed Large Language Models. CoRR Xinyuan Wang, Yanchi Liu, Wei Cheng, Xujiang Zhao, Zhengzhang Chen, Wenchao Yu, Yanjie Fu, Haifeng Chen
2025	J	`jnl`	Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models. CoRR Zhixia He, Chen Zhao, Minglai Shao, Xintao Wu, Xujiang Zhao, Dong Li, Qin Tian, Linlin Yu
2025	—	`conf`	Position Really Matters: Towards a Holistic Approach for Prompt Tuning. NAACL (Findings) Xianjun Yang, Wei Cheng, Xujiang Zhao, Wenchao Yu, Linda Ruth Petzold, Haifeng Chen
2025	J	`jnl`	Representation Interventions Enable Lifelong Unstructured Knowledge Control. CoRR Xuyuan Liu, Zhengzhang Chen, Xinshuai Dong, Yanchi Liu, Xujiang Zhao, Shengyu Chen, Haoyu Wang, Yujun Yan, Haifeng Chen
2025	A*	`conf`	SFS: Smarter Code Space Search improves LLM Inference Scaling. ICLR Jonathan Light, Yue Wu, Yiyou Sun, Wenchao Yu, Yanchi Liu, Xujiang Zhao, Ziniu Hu, Haifeng Chen, Wei Cheng
2025	J	`jnl`	SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search. CoRR Dong Li, Xujiang Zhao, Linlin Yu, Yanchi Liu, Wei Cheng, Zhengzhang Chen, Zhong Chen, Feng Chen, Chen Zhao, Haifeng Chen
2025	—	`conf`	Uncertainty Propagation on LLM Agent. ACL (1) Qiwei Zhao, Dong Li, Yanchi Liu, Wei Cheng, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Huaxiu Yao, Chen Zhao, Haifeng Chen, Xujiang Zhao
2024	A*	`conf`	3rd Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM). KDD Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Wei Hua, Haifeng Chen
2024	J	`jnl`	A survey on uncertainty reasoning and quantification in belief theory and its application to deep learning. Inf. Fusion Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Qi Zhang, Lance M. Kaplan, Audun Jøsang, Dong Hyun Jeong, Feng Chen, Jin-Hee Cho
2024	J	`jnl`	Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation. CoRR Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu, Junxiang Wang, Xiang Zhang, Suhang Wang, Haifeng Chen
2024	A*	`conf`	Large Language Models Can Be Contextual Privacy Protection Learners. EMNLP Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Quanquan Gu, Haifeng Chen, Wei Wang, Wei Cheng
2024	—	`conf`	Pruning as a Domain-specific LLM Extractor. NAACL-HLT (Findings) Nan Zhang, Yanchi Liu, Xujiang Zhao, Wei Cheng, Runxue Bao, Rui Zhang, Prasenjit Mitra, Haifeng Chen
2024	J	`jnl`	Pruning as a Domain-specific LLM Extractor. CoRR Nan Zhang, Yanchi Liu, Xujiang Zhao, Wei Cheng, Runxue Bao, Rui Zhang, Prasenjit Mitra, Haifeng Chen
2024	J	`jnl`	Quantifying uncertainty in graph neural network explanations. Frontiers Big Data Junji Jiang, Chen Ling, Hongyi Li, Guangji Bai, Xujiang Zhao, Liang Zhao
2024	J	`jnl`	RIO-CPD: A Riemannian Geometric Method for Correlation-aware Online Change Point Detection. CoRR Chengyuan Deng, Zhengzhang Chen, Xujiang Zhao, Haoyu Wang, Junxiang Wang, Haifeng Chen, Jie Gao
2024	J	`jnl`	SAUP: Situation Awareness Uncertainty Propagation on LLM Agent. CoRR Qiwei Zhao, Xujiang Zhao, Yanchi Liu, Wei Cheng, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Huaxiu Yao, Haifeng Chen
2024	J	`jnl`	Scattered Forest Search: Smarter Code Space Exploration with LLMs. CoRR Jonathan Light, Yue Wu, Yiyou Sun, Wenchao Yu, Yanchi Liu, Xujiang Zhao, Ziniu Hu, Haifeng Chen, Wei Cheng
2024	A*	`conf`	Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments. IJCAI Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen
2024	J	`jnl`	Uncertainty Decomposition and Quantification for In-Context Learning of Large Language Models. CoRR Chen Ling, Xujiang Zhao, Wei Cheng, Yanchi Liu, Yiyou Sun, Xuchao Zhang, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen
2024	—	`conf`	Uncertainty Quantification for In-Context Learning of Large Language Models. NAACL-HLT Chen Ling, Xujiang Zhao, Xuchao Zhang, Wei Cheng, Yanchi Liu, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen
2023	A*	`conf`	2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making. KDD Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Haifeng Chen
2023	A	`conf`	Adaptation Speed Analysis for Fairness-aware Causal Models. CIKM Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen
2023	J	`jnl`	Adaptation Speed Analysis for Fairness-aware Causal Models. CoRR Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen
2023	J	`jnl`	Beyond One-Model-Fits-All: A Survey of Domain Specialization for Large Language Models. CoRR Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Carl Yang, Liang Zhao
2023	A	`conf`	Calibrate Graph Neural Networks under Out-of-Distribution Nodes via Deep Q-learning. CIKM Weili Shi, Xueying Yang, Xujiang Zhao, Haifeng Chen, Zhiqiang Tao, Sheng Li
2023	J	`jnl`	Dynamic Prompting: A Unified Framework for Prompt Tuning. CoRR Xianjun Yang, Wei Cheng, Xujiang Zhao, Linda R. Petzold, Haifeng Chen
2023	J	`jnl`	Improving Open Information Extraction with Large Language Models: A Study on Demonstration Uncertainty. CoRR Chen Ling, Xujiang Zhao, Xuchao Zhang, Yanchi Liu, Wei Cheng, Haoyu Wang, Zhengzhang Chen, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
2023	J	`jnl`	Knowledge-enhanced Neural Machine Reasoning: A Review. CoRR Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao
2023	J	`jnl`	Large Language Models Can Be Good Privacy Protection Learners. CoRR Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Haifeng Chen, Wei Wang, Wei Cheng
2023	Misc	`conf`	Multi-Label Temporal Evidential Neural Networks for Early Event Detection. ICASSP Xujiang Zhao, Xuchao Zhang, Chen Zhao, Jin-Hee Cho, Lance M. Kaplan, Dong Hyun Jeong, Audun Jøsang, Haifeng Chen, Feng Chen
2023	J	`jnl`	Multidimensional Uncertainty Quantification for Deep Neural Networks. CoRR Xujiang Zhao
2023	—	`conf`	Open-ended Commonsense Reasoning with Unrestricted Answer Candidates. EMNLP (Findings) Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
2023	J	`jnl`	Open-ended Commonsense Reasoning with Unrestricted Answer Scope. CoRR Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu, Wei Cheng, Mika Oishi, Takao Osaki, Katsushi Matsuda, Haifeng Chen, Liang Zhao
2023	J	`jnl`	Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains. CoRR Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen
2022	J	`jnl`	A Survey on Uncertainty Reasoning and Quantification for Decision Making: Belief Theory Meets Deep Learning. CoRR Zhen Guo, Zelin Wan, Qisheng Zhang, Xujiang Zhao, Feng Chen, Jin-Hee Cho, Qi Zhang, Lance M. Kaplan, Dong Hyun Jeong, Audun Jøsang
2022	A	`conf`	Calibrate Automated Graph Neural Network via Hyperparameter Uncertainty. CIKM Xueying Yang, Jiamian Wang, Xujiang Zhao, Sheng Li, Zhiqiang Tao
2022	A*	`conf`	How Out-of-Distribution Data Hurts Semi-Supervised Learning. ICDM Xujiang Zhao, Krishnateja Killamsetty, Rishabh K. Iyer, Feng Chen
2022	—	`conf`	Layer Adaptive Deep Neural Networks for Out-of-Distribution Detection. PAKDD (2) Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen
2022	J	`jnl`	Layer Adaptive Deep Neural Networks for Out-of-distribution Detection. CoRR Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen
2022	J	`jnl`	SEED: Sound Event Early Detection via Evidential Uncertainty. CoRR Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen
2022	Misc	`conf`	Seed: Sound Event Early Detection Via Evidential Uncertainty. ICASSP Xujiang Zhao, Xuchao Zhang, Wei Cheng, Wenchao Yu, Yuncong Chen, Haifeng Chen, Feng Chen
2021	—	`conf`	Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. EMNLP (1) Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi
2021	J	`jnl`	Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation. CoRR Liyan Xu, Xuchao Zhang, Xujiang Zhao, Haifeng Chen, Feng Chen, Jinho D. Choi
2021	A*	`conf`	CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining. WWW Zhuoyi Wang, Yuqiao Chen, Chen Zhao, Yu Lin, Xujiang Zhao, Hemeng Tao, Yigong Wang, Latifur Khan
2021	A*	`conf`	Multidimensional Uncertainty-Aware Evidential Neural Networks. AAAI Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen
2021	A*	`conf`	RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. NeurIPS Krishnateja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
2021	J	`jnl`	RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning. CoRR Krishnateja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh K. Iyer
2020	J	`jnl`	Multidimensional Uncertainty-Aware Evidential Neural Networks. CoRR Yibo Hu, Yuzhe Ou, Xujiang Zhao, Jin-Hee Cho, Feng Chen
2020	A*	`conf`	Multifaceted Uncertainty Estimation for Label-Efficient Deep Learning. NeurIPS Weishi Shi, Xujiang Zhao, Feng Chen, Qi Yu
2020	J	`jnl`	Robust Semi-Supervised Learning with Out of Distribution Data. CoRR Xujiang Zhao, Krishnateja Killamsetty, Rishabh K. Iyer, Feng Chen
2020	A*	`conf`	Uncertainty Aware Semi-Supervised Learning on Graph Data. NeurIPS Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho
2020	J	`jnl`	Uncertainty Aware Semi-Supervised Learning on Graph Data. CoRR Xujiang Zhao, Feng Chen, Shu Hu, Jin-Hee Cho
2019	J	`jnl`	Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data. CoRR Xujiang Zhao, Feng Chen, Jin-Hee Cho
2019	J	`jnl`	Quantifying Classification Uncertainty using Regularized Evidential Neural Networks. CoRR Xujiang Zhao, Yuzhe Ou, Lance M. Kaplan, Feng Chen, Jin-Hee Cho
2019	—	`conf`	Uncertainty-Aware Opinion Inference Under Adversarial Attacks. IEEE BigData Adil Alim, Xujiang Zhao, Jin-Hee Cho, Feng Chen
2019	C	`conf`	Uncertainty-based Decision Making Using Deep Reinforcement Learning. FUSION Xujiang Zhao, Shu Hu, Jin-Hee Cho, Feng Chen
2018	A*	`conf`	Deep Learning Based Scalable Inference of Uncertain Opinions. ICDM Xujiang Zhao, Feng Chen, Jin-Hee Cho
2018	—	`conf`	Deep Learning for Predicting Dynamic Uncertain Opinions in Network Data. IEEE BigData Xujiang Zhao, Feng Chen, Jin-Hee Cho
2018	—	`conf`	Uncertainty-Based Opinion Inference on Network Data Using Graph Convolutional Neural Networks. MILCOM Xujiang Zhao, Feng Chen, Jin-Hee Cho
2017	—	`conf`	Object Detection Based on Deep Feature for Optical Remote Sensing Images. GSKI (1) Xujiang Zhao, Shouhong Wan, Chang Zou, Xingyue Li, Li Yan