Chengyuan Deng

34 papers A* 5A 3B 3Journal 23

Year	Rank	Type	Title / Venue / Authors
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	J	`jnl`	Impossibility of depth reduction in explainable clustering. Inf. Comput. Chengyuan Deng, Surya Teja Gavva, Karthik C. S., Parth Patel, Adarsh Srinivasan
2026	J	`jnl`	Locality Sensitive Hashing in Hyperbolic Space. CoRR Chengyuan Deng, Jie Gao, Kevin Lu, Feng Luo, Cheng Xin
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`	Deconstructing the ethics of large language models from long-standing issues to new-emerging dilemmas: a survey. AI Ethics Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Yichen Wang, Kuofeng Gao, Henry Peng Zou, Yiqiao Jin, Yijia Xiao, Shenghao Wu, Zongxing Xie, Weimin Lyu, Sihong He, Lu Cheng, Haohan Wang, Jun Zhuang
2025	J	`jnl`	Johnson-Lindenstrauss Lemma Beyond Euclidean Geometry. CoRR Chengyuan Deng, Jie Gao, Kevin Lu, Feng Luo, Cheng Xin
2025	A	`conf`	Low Sensitivity Hopsets. ITCS Vikrant Ashvinkumar, Aaron Bernstein, Chengyuan Deng, Jie Gao, Nicole Wein
2025	A*	`conf`	On the Price of Differential Privacy for Hierarchical Clustering. ICLR Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou
2025	J	`jnl`	On the Price of Differential Privacy for Hierarchical Clustering. CoRR Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang, Samson Zhou
2024	J	`jnl`	Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas. CoRR Chengyuan Deng, Yiqun Duan, Xin Jin, Heng Chang, Yijun Tian, Han Liu, Henry Peng Zou, Yiqiao Jin, Yijia Xiao, Yichen Wang, Shenghao Wu, Zongxing Xie, Kuofeng Gao, Sihong He, Jun Zhuang, Lu Cheng, Haohan Wang
2024	J	`jnl`	LEMMA-RCA: A Large Multi-modal Multi-domain Dataset for Root Cause Analysis. CoRR Lecheng Zheng, Zhengzhang Chen, Dongjie Wang, Chengyuan Deng, Reon Matsuoka, Haifeng Chen
2024	J	`jnl`	Low Sensitivity Hopsets. CoRR Vikrant Ashvinkumar, Aaron Bernstein, Chengyuan Deng, Jie Gao, Nicole Wein
2024	A*	`conf`	Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms. NeurIPS Chengyuan Deng, Jie Gao, Kevin Lu, Feng Luo, Hongbin Sun, Cheng Xin
2024	J	`jnl`	Neuc-MDS: Non-Euclidean Multidimensional Scaling Through Bilinear Forms. CoRR Chengyuan Deng, Jie Gao, Kevin Lu, Feng Luo, Hongbin Sun, Cheng Xin
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	A*	`conf`	The Discrepancy of Shortest Paths. ICALP Greg Bodwin, Chengyuan Deng, Jie Gao, Gary Hoppenworth, Jalaj Upadhyay, Chen Wang
2024	J	`jnl`	The Discrepancy of Shortest Paths. CoRR Greg Bodwin, Chengyuan Deng, Jie Gao, Gary Hoppenworth, Jalaj Upadhyay, Chen Wang
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	B	`conf`	Differentially Private Range Query on Shortest Paths. WADS Chengyuan Deng, Jie Gao, Jalaj Upadhyay, Chen Wang
2023	A*	`conf`	E NeurIPS Shihang Feng, Hanchen Wang, Chengyuan Deng, Yinan Feng, Yanhua Liu, Min Zhu, Peng Jin, Yinpeng Chen, Youzuo Lin
2023	J	`jnl`	E CoRR Shihang Feng, Hanchen Wang, Chengyuan Deng, Yinan Feng, Yanhua Liu, Min Zhu, Peng Jin, Yinpeng Chen, Youzuo Lin
2023	A	`conf`	Evaluating Stability in Massive Social Networks: Efficient Streaming Algorithms for Structural Balance. APPROX/RANDOM Vikrant Ashvinkumar, Sepehr Assadi, Chengyuan Deng, Jie Gao, Chen Wang
2023	J	`jnl`	Evaluating Stability in Massive Social Networks: Efficient Streaming Algorithms for Structural Balance. CoRR Vikrant Ashvinkumar, Sepehr Assadi, Chengyuan Deng, Jie Gao, Chen Wang
2023	J	`jnl`	Impossibility of Depth Reduction in Explainable Clustering. CoRR Chengyuan Deng, Surya Teja Gavva, Karthik C. S., Parth Patel, Adarsh Srinivasan
2022	A*	`conf`	OpenFWI: Large-scale Multi-structural Benchmark Datasets for Full Waveform Inversion. NeurIPS Chengyuan Deng, Shihang Feng, Hanchen Wang, Xitong Zhang, Peng Jin, Yinan Feng, Qili Zeng, Yinpeng Chen, Youzuo Lin
2021	J	`jnl`	Adaptive ensemble of classifiers with regularization for imbalanced data classification. Inf. Fusion Chen Wang, Chengyuan Deng, Zhoulu Yu, Dafeng Hui, Xiaofeng Gong, Ruisen Luo
2021	J	`jnl`	On the Robustness and Generalization of Deep Learning Driven Full Waveform Inversion. CoRR Chengyuan Deng, Youzuo Lin
2021	J	`jnl`	OpenFWI: Benchmark Seismic Datasets for Machine Learning-Based Full Waveform Inversion. CoRR Chengyuan Deng, Yinan Feng, Shihang Feng, Peng Jin, Xitong Zhang, Qili Zeng, Youzuo Lin
2020	J	`jnl`	Imbalance-XGBoost: leveraging weighted and focal losses for binary label-imbalanced classification with XGBoost. Pattern Recognit. Lett. Chen Wang, Chengyuan Deng, Suzhen Wang
2020	B	`conf`	On the Global Self-attention Mechanism for Graph Convolutional Networks. ICPR Chen Wang, Chengyuan Deng
2020	J	`jnl`	On the Global Self-attention Mechanism for Graph Convolutional Networks. CoRR Chen Wang, Chengyuan Deng
2020	B	`conf`	SAG-VAE: End-to-end Joint Inference of Data Representations and Feature Relations. IJCNN Chen Wang, Chengyuan Deng, Vladimir Ivanov
2019	J	`jnl`	Imbalance-XGBoost: Leveraging Weighted and Focal Losses for Binary Label-Imbalanced Classification with XGBoost. CoRR Chen Wang, Chengyuan Deng, Suzhen Wang
2019	J	`jnl`	SAG-VAE: End-to-end Joint Inference of Data Representations and Feature Relations. CoRR Chen Wang, Chengyuan Deng, Vladimir Ivanov