Joint-based multi-task sparse learning for human action recognition. - Wenjun Wu; Yanhua Yang; Ruishan Liu; Cheng Deng (ICIMCS, 2015)

Recognizing Human Actions by Sharing Knowledge in Implicit Action Groups. - Ruishan Liu; Yanhua Yang; Cheng Deng (PCM (1), 2015)

Multi-task human action recognition via exploring super-category. - Yanhua Yang; Ruishan Liu; Cheng Deng; Xinbo Gao 001 (Signal Process., 2016)

Personalized Image Annotation Using Deep Architecture. - Fangxiang Feng; Ruishan Liu; Xiaojie Wang 006; Xueming Li; Song Bi (IEEE Access, 2017)

The Effects of Memory Replay in Reinforcement Learning. - Ruishan Liu; James Zou 001 (Allerton, 2018)

Model Compression with Generative Adversarial Networks. - Ruishan Liu; Nicoló Fusi; Lester Mackey (CoRR, 2018)

Learning transport cost from subset correspondence. - Ruishan Liu; Akshay Balsubramani; James Zou 001 (ICLR, 2020)

Data Sculpting: Interpretable Algorithm for End-to-End Cohort Selection. - Ruishan Liu; James Zou 001 (IEEECONF, 2022)

Data-Driven Subgroup Identification for Linear Regression. - Zachary Izzo; Ruishan Liu; James Zou 001 (ICML, 2023)

Cancer-Myth: Evaluating AI Chatbot on Patient Questions with False Presuppositions. - Wang Bill Zhu; Tianqi Chen; Ching Ying Lin; Jade Law; Mazen Jizzini; Jorge J. Nieva; Ruishan Liu; Robin Jia (CoRR, 2025)

CounselBench: A Large-Scale Expert Evaluation and Adversarial Benchmark of Large Language Models in Mental Health Counseling. - Yahan Li; Jifan Yao; John Bosco S. Bunyi; Adam C. Frank; Angel Hwang; Ruishan Liu (CoRR, 2025)