Jiaqi W. Ma

According to our database, Jiaqi W. Ma authored at least 51 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

DATE-LM: Benchmarking Data Attribution Evaluation for Large Language Models.

Cathy Jiao, Yijun Pan, Emily Xiao, Daisy Sheng, Niket Jain, Hanzhang Zhao, Ishita Dasgupta, Jiaqi W. Ma, Chenyan Xiong

CoRR, July, 2025

Accountability Attribution: Tracing Model Behavior to Training Processes.

Shichang Zhang, Hongzhe Du, Karim Saraipour, Jiaqi W. Ma, Himabindu Lakkaraju

CoRR, June, 2025

Taming Hyperparameter Sensitivity in Data Attribution: Practical Selection Without Costly Retraining.

Weiyi Wang, Junwei Deng, Yuzheng Hu, Shiyuan Zhang, Xirui Jiang, Runting Zhang, Han Zhao, Jiaqi W. Ma

CoRR, May, 2025

Daunce: Data Attribution through Uncertainty Estimation.

Xingyuan Pan, Chenlu Ye, Joseph Melkonian, Jiaqi W. Ma, Tong Zhang

CoRR, May, 2025

Measuring Fine-Grained Relatedness in Multitask Learning via Data Attribution.

Yiwen Tu, Ziqi Liu, Jiaqi W. Ma, Weijing Tang

CoRR, May, 2025

A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning.

Yuzheng Hu, Fan Wu, Haotian Ye, David A. Forsyth, James Zou, Nan Jiang, Jiaqi W. Ma, Han Zhao

CoRR, May, 2025

GraSS: Scalable Influence Function with Sparse Gradient Compression.

Pingbang Hu, Joseph Melkonian, Weijing Tang, Han Zhao, Jiaqi W. Ma

CoRR, May, 2025

Efficient Estimation of Shortest-Path Distance Distributions to Samples in Graphs.

Alan Zhu, Jiaqi Ma, Qiaozhu Mei

CoRR, February, 2025

Detecting and Filtering Unsafe Training Data via Data Attribution.

Yijun Pan, Taiwei Shi, Jieyu Zhao, Jiaqi W. Ma

CoRR, February, 2025

Improving Influence-based Instruction Tuning Data Selection for Balanced Learning of Diverse Capabilities.

Qirun Dai, Dylan Zhang, Jiaqi W. Ma, Hao Peng

CoRR, January, 2025

A Versatile Influence Function for Data Attribution with Non-Decomposable Loss.

Junwei Deng, Weijing Tang, Jiaqi W. Ma

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Adversarial Attacks on Data Attribution.

Xinhe Wang, Pingbang Hu, Junwei Deng, Jiaqi W. Ma

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?

Jin Huang, Xingjian Zhang, Qiaozhu Mei, Jiaqi Ma

Trans. Mach. Learn. Res., 2024

DCA-Bench: A Benchmark for Dataset Curation Agents.

Benhao Huang, Yingzhuo Yu, Jin Huang, Xingjian Zhang, Jiaqi Ma

CoRR, 2024

Efficient Ensembles Improve Training Data Attribution.

Junwei Deng, Ting-Wei Li, Shichang Zhang, Jiaqi Ma

CoRR, 2024

OpenHEXAI: An Open-Source Framework for Human-Centered Evaluation of Explainable Machine Learning.

Jiaqi Ma, Vivian Lai, Yiming Zhang, Chacha Chen, Paul Hamilton, Davor Ljubenkov, Himabindu Lakkaraju, Chenhao Tan

CoRR, 2024

PM2.5 forecasting under distribution shift: A graph learning approach.

Yachuan Liu, Jiaqi Ma, Paramveer Dhillon, Qiaozhu Mei

AI Open, 2024

Most Influential Subset Selection: Challenges, Promises, and Beyond.

Yuzheng Hu, Pingbang Hu, Han Zhao, Jiaqi W. Ma

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

dattri: A Library for Efficient Data Attribution.

Junwei Deng, Ting-Wei Li, Shiyuan Zhang, Shixuan Liu, Yijun Pan, Hao Huang, Xinhe Wang, Pingbang Hu, Xingjian Zhang, Jiaqi W. Ma

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Confronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications.

Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Fair Machine Unlearning: Data Removal while Mitigating Disparities.

Alex Oesterling, Jiaqi Ma, Flávio P. Calmon, Himabindu Lakkaraju

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Partition-Based Active Learning for Graph Neural Networks.

Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei

Trans. Mach. Learn. Res., 2023

Computational Copyright: Towards A Royalty Model for AI Music Generation Platforms.

Junwei Deng, Jiaqi Ma

CoRR, 2023

Investigating the Fairness of Large Language Models for Predictions on Tabular Data.

Yanchen Liu, Srishti Gautam, Jiaqi Ma, Himabindu Lakkaraju

CoRR, 2023

Can LLMs Effectively Leverage Graph Structural Information: When and Why.

Jin Huang, Xingjian Zhang, Qiaozhu Mei, Jiaqi Ma

CoRR, 2023

Accurate, Explainable, and Private Models: Providing Recourse While Minimizing Training Data Leakage.

Catherine Huang, Chelse Swoopes, Christina Xiao, Jiaqi Ma, Himabindu Lakkaraju

CoRR, 2023

Analyzing Chain-of-Thought Prompting in Large Language Models via Gradient-based Feature Attributions.

Skyler Wu, Eric Meng Shen, Charumathi Badrinath, Jiaqi Ma, Himabindu Lakkaraju

CoRR, 2023

A Metadata-Driven Approach to Understand Graph Neural Networks.

Ting Wei Li, Qiaozhu Mei, Jiaqi Ma

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Post Hoc Explanations of Language Models Can Improve Language Models.

Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, Himabindu Lakkaraju

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The 3rd Workshop on Graph Learning Benchmarks (GLB 2023).

Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Towards Bridging the Gaps between the Right to Explanation and the Right to be Forgotten.

Satyapriya Krishna, Jiaqi Ma, Himabindu Lakkaraju

Proceedings of the International Conference on Machine Learning, 2023

How Much Space Has Been Explored? Measuring the Chemical Space Covered by Databases and Machine-Generated Molecules.

Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks.

Weijing Tang, Jiaqi Ma, Qiaozhu Mei, Ji Zhu

J. Mach. Learn. Res., 2022

Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling.

Jiaqi Ma, Xingjian Zhang, Qiaozhu Mei

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem.

Jiaqi Ma, Junwei Deng, Qiaozhu Mei

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks.

Jiaqi Ma, Xingjian Zhang, Hezheng Fan, Jin Huang, Tianyue Li, Ting Wei Li, Yiwen Tu, Chenshu Zhu, Qiaozhu Mei

Proceedings of the Learning on Graphs Conference, 2022

2021

How Much of the Chemical Space Has Been Covered? Measuring and Improving the Variety of Candidate Set in Molecular Generation.

Yutong Xie, Ziqiao Xu, Jiaqi Ma, Qiaozhu Mei

CoRR, 2021

GReS: Workshop on Graph Neural Networks for Recommendation and Search.

Thibaut Thonet, Stéphane Clinchant, Carlos Lassance, Elvin Isufi, Jiaqi Ma, Yutong Xie, Jean-Michel Renders, Michael M. Bronstein

Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

Subgroup Generalization and Fairness of Graph Neural Networks.

Jiaqi Ma, Junwei Deng, Qiaozhu Mei

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks.

Jiaqi Ma, Bo Chang, Xuefei Zhang, Qiaozhu Mei

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model.

Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Black-Box Adversarial Attacks on Graph Neural Networks with Limited Node Access.

Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei

CoRR, 2020

Off-policy Learning in Two-stage Recommender Systems.

Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Towards More Practical Adversarial Attacks on Graph Neural Networks.

Jiaqi Ma, Shuangrui Ding, Qiaozhu Mei

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Graph Representation Learning via Multi-task Knowledge Distillation.

Jiaqi Ma, Qiaozhu Mei

CoRR, 2019

A Flexible Generative Framework for Graph-based Semi-supervised Learning.

Jiaqi Ma, Weijing Tang, Ji Zhu, Qiaozhu Mei

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning.

Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts.

Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

DeepCas: An End-to-end Predictor of Information Cascades.

Cheng Li, Jiaqi Ma, Xiaoxiao Guo, Qiaozhu Mei

Proceedings of the 26th International Conference on World Wide Web, 2017

2016

Joint Community and Structural Hole Spanner Detection via Harmonic Modularity.

Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen, Philip S. Yu

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Learning cascaded influence under partial monitoring.

Jie Zhang, Jiaqi Ma, Jie Tang

Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2016