Ke Yang

According to our database, Ke Yang authored at least 31 papers between 2016 and 2026.

Collaborative distances:

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

2026

PlugMem: A Task-Agnostic Plugin Memory Module for LLM Agents.

Ke Yang, Zixi Chen, Xuan He, Jize Jiang, Michel Galley, Chenglong Wang, Jianfeng Gao, Jiawei Han, ChengXiang Zhai

CoRR, March, 2026

2025

Geometric-Disentangelment Unlearning.

Duo Zhou, Yuji Zhang, Tianxin Wei, Ruizhong Qiu, Ke Yang, Xiao Lin, Cheng Qian, Jingrui He, Hanghang Tong, Heng Ji, Huan Zhang

CoRR, November, 2025

ERA: Transforming VLMs into Embodied Agents via Embodied Prior Learning and Online Reinforcement Learning.

Hanyang Chen, Mark Zhao, Rui Yang, Qinwei Ma, Ke Yang, Jiarui Yao, Kangrui Wang, Hao Bai, Zhenhailong Wang, Rui Pan, Mengchao Zhang, Jose A. Barreiros, Aykut Özgün Önol, ChengXiang Zhai, Heng Ji, Manling Li, Huan Zhang, Tong Zhang

CoRR, October, 2025

Ten Principles of AI Agent Economics.

Ke Yang, ChengXiang Zhai

CoRR, May, 2025

JIR-Arena: The First Benchmark Dataset for Just-in-time Information Recommendation.

Ke Yang, Kevin Ros, Shankar Kumar Senthil Kumar, ChengXiang Zhai

CoRR, May, 2025

Perception-aware Sampling for Scatterplot Visualizations.

Zafeiria Moumoulidou, Hamza Elhamdadi, Ke Yang, Subrata Mitra, Cindy Xiong Bearfield, Alexandra Meliou

CoRR, April, 2025

TinyHelen's First Curriculum: Training and Evaluating Tiny Language Models in a Simpler Language Environment.

Ke Yang, Volodymyr V. Kindratenko, ChengXiang Zhai

CoRR, January, 2025

AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents.

Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement.

Chenkai Sun, Ke Yang, Revanth Gangi Reddy, Yi Ren Fung, Hou Pong Chan, Kevin Small, ChengXiang Zhai, Heng Ji

Proceedings of the 31st International Conference on Computational Linguistics, 2025

Extracting Causal Relational Rules for Medical Question-Answering Tasks using Large Language Models.

Md Sohanur Rahman, Yuexia Zhang, Anthony Rios, Ke Yang

Proceedings of the ACM/IEEE International Conference on Connected Health: Applications, 2025

ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study.

Eric Modesitt, Ke Yang, Spencer Hulsey, Xin Liu, ChengXiang Zhai, Volodymyr V. Kindratenko

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study.

Eric Modesitt, Ke Yang, Spencer Hulsey, Chengxiang Zhai, Volodymyr V. Kindratenko

CoRR, 2024

Prejudice and Caprice: A Statistical Framework for Measuring Social Discrimination in Large Language Models.

Yiran Liu, Ke Yang, Zehan Qi, Xiao Liu, Yang Yu, Chengxiang Zhai

CoRR, 2024

Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement.

Chenkai Sun, Ke Yang, Revanth Gangi Reddy, Yi R. Fung, Hou Pong Chan, ChengXiang Zhai, Heng Ji

CoRR, 2024

If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents.

Ke Yang, Jiateng Liu, John Wu, Chaoqi Yang, Yi R. Fung, Sha Li, Zixuan Huang, Xu Cao, Xingyao Wang, Yiquan Wang, Heng Ji, Chengxiang Zhai

CoRR, 2024

DEEILS: Data Ethics Embedded Interactive Learning System for Computer Science Students.

Ke Yang

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Bias and Volatility: A Statistical Framework for Evaluating Large Language Model's Stereotypes and the Associated Generation Inconsistency.

Yiran Liu, Ke Yang, Zehan Qi, Xiao Liu, Yang Yu, Cheng Xiang Zhai

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Non-Invasive Fairness in Learning Through the Lens of Data Drift.

Ke Yang, Alexandra Meliou

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

Fairness in Ranking, Part I: Score-Based Ranking.

Meike Zehlike, Ke Yang, Julia Stoyanovich

ACM Comput. Surv., 2023

Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems.

Meike Zehlike, Ke Yang, Julia Stoyanovich

ACM Comput. Surv., 2023

Tutorials at The Web Conference 2023.

Valeria Fionda, Olaf Hartig, Reyhaneh Abdolazimi, Sihem Amer-Yahia, Hongzhi Chen, Xiao Chen, Peng Cui, Jeffrey Dalton, Xin Luna Dong, Lisette Espín-Noboa, Wenqi Fan, Manuela Fritz, Quan Gan, Jingtong Gao, Xiaojie Guo, Torsten Hahmann, Jiawei Han, Soyeon Caren Han, Estevam Hruschka, Liang Hu, Jiaxin Huang, Utkarshani Jaimini, Olivier Jeunen, Yushan Jiang, Fariba Karimi, George Karypis, Krishnaram Kenthapadi, Himabindu Lakkaraju, Hady W. Lauw, Thai Le, Trung-Hoang Le, Dongwon Lee, Geon Lee, Liat Levontin, Cheng-Te Li, Haoyang Li, Ying Li, Jay Chiehen Liao, Qidong Liu, Usha Lokala, Ben London, Siqu Long, Hande Küçük-McGinty, Yu Meng, Seungwhan Moon, Usman Naseem, Pradeep Natarajan, Behrooz Omidvar-Tehrani, Zijie Pan, Devesh Parekh, Jian Pei, Tiago Peixoto, Steven Pemberton, Josiah Poon, Filip Radlinski, Federico Rossetto, Kaushik Roy, Aghiles Salah, Mehrnoosh Sameki, Amit P. Sheth, Cogan Shimizu, Kijung Shin, Dongjin Song, Julia Stoyanovich, Dacheng Tao, Johanne R. Trippas, Quoc Truong, Yu-Che Tsai, Adaku Uchendu, Bram van den Akker, Lin Wang, Minjie Wang, Shoujin Wang, Xin Wang, Ingmar Weber, Henry Weld, Lingfei Wu, Da Xu, Yifan Ethan Xu, Shuyuan Xu, Bo Yang, Ke Yang, Elad Yom-Tov, Jaemin Yoo, Zhou Yu, Reza Zafarani, Hamed Zamani, Meike Zehlike, Qi Zhang, Xikun Zhang, Yongfeng Zhang, Yu Zhang, Zheng Zhang, Liang Zhao, Xiangyu Zhao, Wenwu Zhu

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Fairness in Ranking: From Values to Technical Choices and Back.

Julia Stoyanovich, Meike Zehlike, Ke Yang

Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

ADEPT: A DEbiasing PrompT Framework.

Ke Yang, Charles Yu, Yi Ren Fung, Manling Li, Heng Ji

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

Fairness in Ranking: A Survey.

Meike Zehlike, Ke Yang, Julia Stoyanovich

CoRR, 2021

Causal Intersectionality and Fair Ranking.

Ke Yang, Joshua R. Loftus, Julia Stoyanovich

Proceedings of the 2nd Symposium on Foundations of Responsible Computing, 2021

2020

Causal intersectionality for fair ranking.

Ke Yang, Joshua R. Loftus, Julia Stoyanovich

CoRR, 2020

2019

Balanced Ranking with Diversity Constraints.

Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

A Nutritional Label for Rankings.

Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, Gerome Miklau

Proceedings of the 2018 International Conference on Management of Data, 2018

Online Set Selection with Fairness and Diversity Constraints.

Julia Stoyanovich, Ke Yang, H. V. Jagadish

Proceedings of the 21st International Conference on Extending Database Technology, 2018

2017

Measuring Fairness in Ranked Outputs.

Ke Yang, Julia Stoyanovich

Proceedings of the 29th International Conference on Scientific and Statistical Database Management, 2017

2016

Probabilistic graphical model for detecting spammers in microblog websites.

Zhongming Han, Ke Yang, Fengmin Xu, Dagao Duan

Int. J. Embed. Syst., 2016