Ke Yang - RankMe

37 papers A* 5B 4Journal 22Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	PlugMem: A Task-Agnostic Plugin Memory Module for LLM Agents. CoRR Ke Yang, Zixi Chen, Xuan He, Jize Jiang, Michel Galley, Chenglong Wang, Jianfeng Gao, Jiawei Han, ChengXiang Zhai
2025	A*	`conf`	AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. ICLR Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala
2025	J	`jnl`	ERA: Transforming VLMs into Embodied Agents via Embodied Prior Learning and Online Reinforcement Learning. CoRR 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
2025	B	`conf`	Extracting Causal Relational Rules for Medical Question-Answering Tasks using Large Language Models. CHASE Md Sohanur Rahman, Yuexia Zhang, Anthony Rios, Ke Yang
2025	J	`jnl`	Geometric-Disentangelment Unlearning. CoRR Duo Zhou, Yuji Zhang, Tianxin Wei, Ruizhong Qiu, Ke Yang, Xiao Lin, Cheng Qian, Jingrui He, Hanghang Tong, Heng Ji, Huan Zhang
2025	J	`jnl`	JIR-Arena: The First Benchmark Dataset for Just-in-time Information Recommendation. CoRR Ke Yang, Kevin Ros, Shankar Kumar Senthil Kumar, ChengXiang Zhai
2025	—	`conf`	ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study. ACL (Findings) Eric Modesitt, Ke Yang, Spencer Hulsey, Xin Liu, ChengXiang Zhai, Volodymyr V. Kindratenko
2025	J	`jnl`	Perception-aware Sampling for Scatterplot Visualizations. CoRR Zafeiria Moumoulidou, Hamza Elhamdadi, Ke Yang, Subrata Mitra, Cindy Xiong Bearfield, Alexandra Meliou
2025	B	`conf`	Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement. COLING Chenkai Sun, Ke Yang, Revanth Gangi Reddy, Yi Ren Fung, Hou Pong Chan, Kevin Small, ChengXiang Zhai, Heng Ji
2025	J	`jnl`	Ten Principles of AI Agent Economics. CoRR Ke Yang, ChengXiang Zhai
2025	J	`jnl`	TinyHelen's First Curriculum: Training and Evaluating Tiny Language Models in a Simpler Language Environment. CoRR Ke Yang, Volodymyr V. Kindratenko, ChengXiang Zhai
2024	J	`jnl`	AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. CoRR Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala
2024	A*	`conf`	Bias and Volatility: A Statistical Framework for Evaluating Large Language Model's Stereotypes and the Associated Generation Inconsistency. NeurIPS Yiran Liu, Ke Yang, Zehan Qi, Xiao Liu, Yang Yu, Cheng Xiang Zhai
2024	—	`conf`	DEEILS: Data Ethics Embedded Interactive Learning System for Computer Science Students. SIGCSE (2) Ke Yang
2024	J	`jnl`	If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents. CoRR 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
2024	A*	`conf`	Non-Invasive Fairness in Learning Through the Lens of Data Drift. ICDE Ke Yang, Alexandra Meliou
2024	J	`jnl`	ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain Adaptation with an Astronomy Case Study. CoRR Eric Modesitt, Ke Yang, Spencer Hulsey, ChengXiang Zhai, Volodymyr V. Kindratenko
2024	J	`jnl`	Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement. CoRR Chenkai Sun, Ke Yang, Revanth Gangi Reddy, Yi R. Fung, Hou Pong Chan, ChengXiang Zhai, Heng Ji
2024	J	`jnl`	Prejudice and Caprice: A Statistical Framework for Measuring Social Discrimination in Large Language Models. CoRR Yiran Liu, Ke Yang, Zehan Qi, Xiao Liu, Yang Yu, ChengXiang Zhai
2023	A*	`conf`	ADEPT: A DEbiasing PrompT Framework. AAAI Ke Yang, Charles Yu, Yi Ren Fung, Manling Li, Heng Ji
2023	J	`jnl`	Fairness in Ranking, Part I: Score-Based Ranking. ACM Comput. Surv. Meike Zehlike, Ke Yang, Julia Stoyanovich
2023	J	`jnl`	Fairness in Ranking, Part II: Learning-to-Rank and Recommender Systems. ACM Comput. Surv. Meike Zehlike, Ke Yang, Julia Stoyanovich
2023	—	`conf`	Fairness in Ranking: From Values to Technical Choices and Back. SIGMOD Conference Companion Julia Stoyanovich, Meike Zehlike, Ke Yang
2023	J	`jnl`	Non-Invasive Fairness in Learning through the Lens of Data Drift. CoRR Ke Yang, Alexandra Meliou
2023	—	`conf`	Tutorials at The Web Conference 2023. WWW (Companion Volume) 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
2022	J	`jnl`	ADEPT: A DEbiasing PrompT Framework. CoRR Ke Yang, Charles Yu, Yi R. Fung, Manling Li, Heng Ji
2021	—	`conf`	Causal Intersectionality and Fair Ranking. FORC Ke Yang, Joshua R. Loftus, Julia Stoyanovich
2021	J	`jnl`	Fairness in Ranking: A Survey. CoRR Meike Zehlike, Ke Yang, Julia Stoyanovich
2020	J	`jnl`	Causal intersectionality for fair ranking. CoRR Ke Yang, Joshua R. Loftus, Julia Stoyanovich
2019	A*	`conf`	Balanced Ranking with Diversity Constraints. IJCAI Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich
2019	J	`jnl`	Balanced Ranking with Diversity Constraints. CoRR Ke Yang, Vasilis Gkatzelis, Julia Stoyanovich
2018	—	`conf`	A Nutritional Label for Rankings. SIGMOD Conference Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, Gerome Miklau
2018	J	`jnl`	A Nutritional Label for Rankings. CoRR Ke Yang, Julia Stoyanovich, Abolfazl Asudeh, Bill Howe, H. V. Jagadish, Gerome Miklau
2018	B	`conf`	Online Set Selection with Fairness and Diversity Constraints. EDBT Julia Stoyanovich, Ke Yang, H. V. Jagadish
2017	B	`conf`	Measuring Fairness in Ranked Outputs. SSDBM Ke Yang, Julia Stoyanovich
2016	J	`jnl`	Measuring Fairness in Ranked Outputs. CoRR Ke Yang, Julia Stoyanovich
2016	J	`jnl`	Probabilistic graphical model for detecting spammers in microblog websites. Int. J. Embed. Syst. Zhongming Han, Ke Yang, Fengmin Xu, Dagao Duan