Jiaqi Ma - RankMe

53 papers A* 14A 5B 1Journal 31Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Copyright Detective: A Forensic System to Evidence LLMs Flickering Copyright Leakage Risks. CoRR Guangwei Zhang, Jianing Zhu, Cheng Qian, Neil Gong, Rada Mihalcea, Zhaozhuo Xu, Jingrui He, Jiaqi Ma, Yun Huang, Chaowei Xiao, Bowen Li, Ahmed Abbasi, Dongwon Lee, Heng Ji, Denghui Zhang
2025	J	`jnl`	Efficient Estimation of Shortest-Path Distance Distributions to Samples in Graphs. CoRR Alan Zhu, Jiaqi Ma, Qiaozhu Mei
2024	J	`jnl`	Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why? Trans. Mach. Learn. Res. Jin Huang, Xingjian Zhang, Qiaozhu Mei, Jiaqi Ma
2024	—	`conf`	Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications. NAACL-HLT Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju
2024	J	`jnl`	DCA-Bench: A Benchmark for Dataset Curation Agents. CoRR Benhao Huang, Yingzhuo Yu, Jin Huang, Xingjian Zhang, Jiaqi Ma
2024	J	`jnl`	Efficient Ensembles Improve Training Data Attribution. CoRR Junwei Deng, Ting-Wei Li, Shichang Zhang, Jiaqi Ma
2024	A	`conf`	Fair Machine Unlearning: Data Removal while Mitigating Disparities. AISTATS Alex Oesterling, Jiaqi Ma, Flávio P. Calmon, Himabindu Lakkaraju
2024	J	`jnl`	OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning. CoRR Jiaqi Ma, Vivian Lai, Yiming Zhang, Chacha Chen, Paul Hamilton, Davor Ljubenkov, Himabindu Lakkaraju, Chenhao Tan
2024	J	`jnl`	PM2.5 forecasting under distribution shift: A graph learning approach. AI Open Yachuan Liu, Jiaqi Ma, Paramveer Dhillon, Qiaozhu Mei
2023	A*	`conf`	A Metadata-Driven Approach to Understand Graph Neural Networks. NeurIPS Ting Wei Li, Qiaozhu Mei, Jiaqi Ma
2023	J	`jnl`	A Metadata-Driven Approach to Understand Graph Neural Networks. CoRR Ting Wei Li, Qiaozhu Mei, Jiaqi Ma
2023	J	`jnl`	Accurate, Explainable, and Private Models: Providing Recourse While Minimizing Training Data Leakage. CoRR Catherine Huang, Chelse Swoopes, Christina Xiao, Jiaqi Ma, Himabindu Lakkaraju
2023	J	`jnl`	Analyzing Chain-of-Thought Prompting in Large Language Models via Gradient-based Feature Attributions. CoRR Skyler Wu, Eric Meng Shen, Charumathi Badrinath, Jiaqi Ma, Himabindu Lakkaraju
2023	J	`jnl`	Can LLMs Effectively Leverage Graph Structural Information: When and Why. CoRR Jin Huang, Xingjian Zhang, Qiaozhu Mei, Jiaqi Ma
2023	J	`jnl`	Computational Copyright: Towards A Royalty Model for AI Music Generation Platforms. CoRR Junwei Deng, Jiaqi Ma
2023	J	`jnl`	Fair Machine Unlearning: Data Removal while Mitigating Disparities. CoRR Alex Oesterling, Jiaqi Ma, Flávio P. Calmon, Hima Lakkaraju
2023	A*	`conf`	How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules. ICLR Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei
2023	J	`jnl`	Investigating the Fairness of Large Language Models for Predictions on Tabular Data. CoRR Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju
2023	J	`jnl`	Partition-Based Active Learning for Graph Neural Networks. Trans. Mach. Learn. Res. Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei
2023	A*	`conf`	Post Hoc Explanations of Language Models Can Improve Language Models. NeurIPS Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju
2023	J	`jnl`	Post Hoc Explanations of Language Models Can Improve Language Models. CoRR Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju
2023	A*	`conf`	The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik
2023	A*	`conf`	Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten. ICML Satyapriya Krishna, Jiaqi Ma, Himabindu Lakkaraju
2023	J	`jnl`	Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten. CoRR Satyapriya Krishna, Jiaqi Ma, Himabindu Lakkaraju
2022	A	`conf`	Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem. WSDM Jiaqi Ma, Junwei Deng, Qiaozhu Mei
2022	A	`conf`	Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling. WSDM Jiaqi Ma, Xingjian Zhang, Qiaozhu Mei
2022	—	`conf`	Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks. LoG Jiaqi Ma, Xingjian Zhang, Hezheng Fan, Jin Huang, Tianyue Li, Ting Wei Li, Yiwen Tu, Chenshu Zhu, Qiaozhu Mei
2022	J	`jnl`	Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks. CoRR Jiaqi Ma, Xingjian Zhang, Hezheng Fan, Jin Huang, Tianyue Li, Ting Wei Li, Yiwen Tu, Chenshu Zhu, Qiaozhu Mei
2022	J	`jnl`	Partition-Based Active Learning for Graph Neural Networks. CoRR Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei
2022	J	`jnl`	SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks. J. Mach. Learn. Res. Weijing Tang, Jiaqi Ma, Qiaozhu Mei, Ji Zhu
2021	J	`jnl`	Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem. CoRR Jiaqi Ma, Junwei Deng, Qiaozhu Mei
2021	A*	`conf`	CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks. ICLR Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei
2021	J	`jnl`	Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling. CoRR Jiaqi Ma, Xingjian Zhang, Qiaozhu Mei
2021	A	`conf`	GReS: Workshop on Graph Neural Networks for Recommendation and Search. RecSys Thibaut Thonet, Stéphane Clinchant, Carlos Lassance, Elvin Isufi, Jiaqi Ma, Yutong Xie, Jean-Michel Renders, Michael M. Bronstein
2021	J	`jnl`	How Much of the Chemical Space Has Been Covered? Measuring and Improving the Variety of Candidate Set in Molecular Generation. CoRR Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei
2021	A	`conf`	Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. AISTATS Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei
2021	A*	`conf`	Subgroup Generalization and Fairness of Graph Neural Networks. NeurIPS Jiaqi Ma, Junwei Deng, Qiaozhu Mei
2021	J	`jnl`	Subgroup Generalization and Fairness of Graph Neural Networks. CoRR Jiaqi Ma, Junwei Deng, Qiaozhu Mei
2020	J	`jnl`	Black-Box Adversarial Attacks on Graph Neural Networks with Limited Node Access. CoRR Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei
2020	J	`jnl`	CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks. CoRR Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei
2020	J	`jnl`	Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. CoRR Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei
2020	A*	`conf`	Off-policy Learning in Two-stage Recommender Systems. WWW Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi
2020	J	`jnl`	SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks. CoRR Weijing Tang, Jiaqi Ma, Qiaozhu Mei, Ji Zhu
2020	A*	`conf`	Towards More Practical Adversarial Attacks on Graph Neural Networks. NeurIPS Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei
2019	A*	`conf`	A Flexible Generative Framework for Graph-based Semi-supervised Learning. NeurIPS Jiaqi Ma, Weijing Tang, Ji Zhu, Qiaozhu Mei
2019	J	`jnl`	A Flexible Generative Framework for Graph-based Semi-supervised Learning. CoRR Jiaqi Ma, Weijing Tang, Ji Zhu, Qiaozhu Mei
2019	J	`jnl`	Graph Representation Learning via Multi-task Knowledge Distillation. CoRR Jiaqi Ma, Qiaozhu Mei
2019	A*	`conf`	SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning. AAAI Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi
2018	A*	`conf`	Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. KDD Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi
2017	A*	`conf`	DeepCas: An End-to-end Predictor of Information Cascades. WWW Cheng Li, Jiaqi Ma, Xiaoxiao Guo, Qiaozhu Mei
2016	J	`jnl`	DeepCas: an End-to-end Predictor of Information Cascades. CoRR Cheng Li, Jiaqi Ma, Xiaoxiao Guo, Qiaozhu Mei
2016	A*	`conf`	Joint Community and Structural Hole Spanner Detection via Harmonic Modularity. KDD Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen, Philip S. Yu
2016	B	`conf`	Learning cascaded influence under partial monitoring. ASONAM Jie Zhang, Jiaqi Ma, Jie Tang