Qiongxiu Li - RankMe

58 papers A* 2Misc 7Journal 36Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	APEX: Probing Neural Networks via Activation Perturbation. CoRR Tao Ren, Xiaoyu Luo, Qiongxiu Li
2026	J	`jnl`	Characterizing Memorization in Diffusion Language Models: Generalized Extraction and Sampling Effects. CoRR Xiaoyu Luo, Wenrui Yu, Qiongxiu Li, Johannes Bjerva
2026	J	`jnl`	Do LLMs Really Memorize Personally Identifiable Information? Revisiting PII Leakage with a Cue-Controlled Memorization Framework. CoRR Xiaoyu Luo, Yiyi Chen, Qiongxiu Li, Johannes Bjerva
2026	J	`jnl`	SOMP: Scalable Gradient Inversion for Large Language Models via Subspace-Guided Orthogonal Matching Pursuit. CoRR Yibo Li, Qiongxiu Li
2026	J	`jnl`	Semantic Leakage from Image Embeddings. CoRR Yiyi Chen, Qiongkai Xu, Desmond Elliott, Qiongxiu Li, Johannes Bjerva
2026	J	`jnl`	When Is Distributed Nonlinear Aggregation Private? Optimality and Information-Theoretical Bounds. CoRR Wenrui Yu, Jaron Skovsted Gundersen, Richard Heusdens, Qiongxiu Li
2025	A*	`conf`	ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification. ICLR Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yingzhe He, Jie Shi, Xiaolin Hu
2025	J	`jnl`	Breaking Privacy in Federated Clustering: Perfect Input Reconstruction via Temporal Correlations. CoRR Guang Yang, Lixia Luo, Qiongxiu Li
2025	—	`conf`	Byzantine-Resilient Federated Learning via Distributed Optimization. EUSIPCO Yufei Xia, Wenrui Yu, Qiongxiu Li
2025	J	`jnl`	Byzantine-Resilient Federated Learning via Distributed Optimization. CoRR Yufei Xia, Wenrui Yu, Qiongxiu Li
2025	—	`conf`	Demem: Privacy-Enhanced Robust Adversarial Learning via De-Memorization. MLSP Xiaoyu Luo, Qiongxiu Li
2025	J	`jnl`	From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges. CoRR Qiongxiu Li, Wenrui Yu, Yufei Xia, Jun Pang
2025	J	`jnl`	LAGO: Few-shot Crosslingual Embedding Inversion Attacks via Language Similarity-Aware Graph Optimization. CoRR Wenrui Yu, Yiyi Chen, Johannes Bjerva, Sokol Kosta, Qiongxiu Li
2025	—	`conf`	Large Language Models are Easily Confused: A Quantitative Metric, Security Implications and Typological Analysis. NAACL (Findings) Yiyi Chen, Qiongxiu Li, Russa Biswas, Johannes Bjerva
2025	—	`conf`	On the Privacy-Robustness Trade-Off in Distributed Average Consensus. EUSIPCO Zarè Palanciyan, Qiongxiu Li, Richard Heusdens
2025	—	`conf`	Optimal Privacy-Preserving Distributed Median Consensus. EUSIPCO Wenrui Yu, Qiongxiu Li, Richard Heusdens, Sokol Kosta
2025	Misc	`conf`	Privacy-Preserving Distributed Maximum Consensus Without Accuracy Loss. ICASSP Wenrui Yu, Richard Heusdens, Jun Pang, Qiongxiu Li
2025	J	`jnl`	Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization. IEEE Trans. Inf. Forensics Secur. Wenrui Yu, Qiongxiu Li, Milan Lopuhaä-Zwakenberg, Mads Græsbøll Christensen, Richard Heusdens
2025	Misc	`conf`	Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study. ICASSP Changlong Ji, Richard Heusdens, Stephane Maag, Qiongxiu Li
2025	A*	`conf`	Shared Path: Unraveling Memorization in Multilingual LLMs through Language Similarities. EMNLP Xiaoyu Luo, Yiyi Chen, Johannes Bjerva, Qiongxiu Li
2025	J	`jnl`	Shared Path: Unraveling Memorization in Multilingual LLMs through Language Similarities. CoRR Xiaoyu Luo, Yiyi Chen, Johannes Bjerva, Qiongxiu Li
2025	J	`jnl`	Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond. CoRR Qiongxiu Li, Xiaoyu Luo, Yiyi Chen, Johannes Bjerva
2024	J	`jnl`	ADBM: Adversarial diffusion bridge model for reliable adversarial purification. CoRR Xiao Li, Wenxuan Sun, Huanran Chen, Qiongxiu Li, Yining Liu, Yingzhe He, Jie Shi, Xiaolin Hu
2024	J	`jnl`	Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus. IEEE Trans. Inf. Forensics Secur. Qiongxiu Li, Jaron Skovsted Gundersen, Milan Lopuhaä-Zwakenberg, Richard Heusdens
2024	J	`jnl`	An Intelligent Innovation Dataset on Scientific Research Outcomes. CoRR Xinran Wu, Hui Zou, Yidan Xing, Jingjing Qu, Qiongxiu Li, Renxia Xue, Xiaoming Fu
2024	J	`jnl`	DeMem: Privacy-Enhanced Robust Adversarial Learning via De-Memorization. CoRR Xiaoyu Luo, Qiongxiu Li
2024	J	`jnl`	Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models. CoRR Xiao Li, Zhuhong Li, Qiongxiu Li, Bingze Lee, Jinghao Cui, Xiaolin Hu
2024	J	`jnl`	Large Language Models are Easily Confused: A Quantitative Metric, Security Implications and Typological Analysis. CoRR Yiyi Chen, Qiongxiu Li, Russa Biswas, Johannes Bjerva
2024	—	`conf`	On the Privacy Bound of Distributed Optimization and its Application in Federated Learning. EUSIPCO Qiongxiu Li, Milan Lopuhaä-Zwakenberg, Wenrui Yu, Richard Heusdens
2024	J	`jnl`	On the Privacy Effect of Data Enhancement via the Lens of Memorization. IEEE Trans. Inf. Forensics Secur. Xiao Li, Qiongxiu Li, Zhanhao Hu, Xiaolin Hu
2024	Misc	`conf`	On the Privacy of Federated Clustering: a Cryptographic View. ICASSP Qiongxiu Li, Lixia Luo
2024	J	`jnl`	Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem. CoRR Qiongxiu Li, Lixia Luo, Agnese Gini, Changlong Ji, Zhanhao Hu, Xiao Li, Chengfang Fang, Jie Shi, Xiaolin Hu
2024	J	`jnl`	Privacy-Preserving Distributed Maximum Consensus Without Accuracy Loss. CoRR Wenrui Yu, Richard Heusdens, Jun Pang, Qiongxiu Li
2024	Misc	`conf`	Privacy-Preserving Distributed Optimisation using Stochastic PDMM. ICASSP Sebastian O. Jordan, Qiongxiu Li, Richard Heusdens
2024	J	`jnl`	ProP: Efficient Backdoor Detection via Propagation Perturbation for Overparametrized Models. CoRR Tao Ren, Qiongxiu Li
2024	J	`jnl`	Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization. CoRR Wenrui Yu, Qiongxiu Li, Milan Lopuhaä-Zwakenberg, Mads Græsbøll Christensen, Richard Heusdens
2024	J	`jnl`	Re-Evaluating Privacy in Centralized and Decentralized Learning: An Information-Theoretical and Empirical Study. CoRR Changlong Ji, Stephane Maag, Richard Heusdens, Qiongxiu Li
2024	Misc	`conf`	Topology-Dependent Privacy Bound for Decentralized Federated Learning. ICASSP Qiongxiu Li, Wenrui Yu, Changlong Ji, Richard Heusdens
2023	J	`jnl`	Adaptive Differentially Quantized Subspace Perturbation (ADQSP): A Unified Framework for Privacy-Preserving Distributed Average Consensus. CoRR Qiongxiu Li, Jaron Skovsted Gundersen, Milan Lopuhaä-Zwakenberg, Richard Heusdens
2023	J	`jnl`	On the privacy of federated Clustering: A Cryptographic View. CoRR Qiongxiu Li, Lixia Luo
2023	J	`jnl`	Topology-Dependent Privacy Bound For Decentralized Federated Learning. CoRR Qiongxiu Li, Wenrui Yu, Changlong Ji, Richard Heusdens
2022	J	`jnl`	Communication efficient privacy-preserving distributed optimization using adaptive differential quantization. Signal Process. Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
2022	J	`jnl`	On the Privacy Effect of Data Enhancement via the Lens of Memorization. CoRR Xiao Li, Qiongxiu Li, Zhanhao Hu, Xiaolin Hu
2022	Misc	`conf`	Privacy-Preserving Distributed Expectation Maximization for Gaussian Mixture Model Using Subspace Perturbation. ICASSP Qiongxiu Li, Jaron Skovsted Gundersen, Katrine Tjell, Rafal Wisniewski, Mads Græsbøll Christensen
2022	J	`jnl`	Privacy-Preserving Distributed Expectation Maximization for Gaussian Mixture Model using Subspace Perturbation. CoRR Qiongxiu Li, Jaron Skovsted Gundersen, Katrine Tjell, Rafal Wisniewski, Mads Græsbøll Christensen
2022	—	`conf`	Two for the price of one: communication efficient and privacy-preserving distributed average consensus using quantization. EUSIPCO Qiongxiu Li, Milan Lopuhaä-Zwakenberg, Richard Heusdens, Mads Græsbøll Christensen
2021	J	`jnl`	Communication efficient privacy-preserving distributed optimization using adaptive differential quantization. CoRR Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
2021	J	`jnl`	Privacy-Preserving Distributed Processing: Metrics, Bounds and Algorithms. IEEE Trans. Inf. Forensics Secur. Qiongxiu Li, Jaron Skovsted Gundersen, Richard Heusdens, Mads Græsbøll Christensen
2020	Misc	`conf`	Convex Optimisation-Based Privacy-Preserving Distributed Average Consensus in Wireless Sensor Networks. ICASSP Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
2020	—	`conf`	Convex optimization-based Privacy-Preserving Distributed Least Squares via Subspace Perturbation. EUSIPCO Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
2020	—	`conf`	Privacy-Preserving Distributed Graph Filtering. EUSIPCO Qiongxiu Li, Mario Coutino, Geert Leus, Mads Græsbøll Christensen
2020	J	`jnl`	Privacy-Preserving Distributed Optimization via Subspace Perturbation: A General Framework. CoRR Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
2020	J	`jnl`	Privacy-Preserving Distributed Optimization via Subspace Perturbation: A General Framework. IEEE Trans. Signal Process. Qiongxiu Li, Richard Heusdens, Mads Græsbøll Christensen
2020	J	`jnl`	Privacy-Preserving Distributed Processing: Metrics, Bounds, and Algorithms. CoRR Qiongxiu Li, Jaron Skovsted Gundersen, Richard Heusdens, Mads Græsbøll Christensen
2019	—	`conf`	A Privacy-Preserving Asynchronous Averaging Algorithm based on Shamir's Secret Sharing. EUSIPCO Qiongxiu Li, Mads Græsbøll Christensen
2019	—	`conf`	Privacy-Preserving Distributed Average Consensus based on Additive Secret Sharing. EUSIPCO Qiongxiu Li, Ignacio Cascudo, Mads Græsbøll Christensen
2016	—	`conf`	Fingerprint Liveness Detection Using CNN Features of Random Sample Patches. BIOSIG Eunsoo Park, Weonjin Kim, Qiongxiu Li, Jungmin Kim, Hakil Kim
2016	—	`conf`	Multi-feature based score fusion method for fingerprint recognition accuracy boosting. APSIPA Qiongxiu Li, Changlong Jin, Weonjin Kim, Jungmin Kim, Shengzhe Li, Hakil Kim