Shared genetic architecture in autoimmune disease - preliminary analysis. - Leqi Liu; Jia Tao 001; Ziyan Yang; Fadi Towfic (BIBM, 2015)

Analyzing Personality through Social Media Profile Picture Choice. - Leqi Liu; Daniel Preotiuc-Pietro; Zahra Riahi Samani; Mohsen Ebrahimi Moghaddam; Lyle H. Ungar (ICWSM, 2016)

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models. - Chen Dan 001; Liu Leqi; Bryon Aragam; Pradeep Ravikumar; Eric P. Xing (NeurIPS, 2018)

Sample Complexity of Nonparametric Semi-Supervised Learning. - Chen Dan 001; Liu Leqi; Bryon Aragam; Pradeep Ravikumar; Eric P. Xing (CoRR, 2018)

On Human-Aligned Risk Minimization. - Liu Leqi; Adarsh Prasad; Pradeep Ravikumar (NeurIPS, 2019)

Game Design for Eliciting Distinguishable Behavior. - Fan Yang 058; Liu Leqi; Yifan Wu; Zachary Chase Lipton; Pradeep Ravikumar; Tom M. Mitchell; William W. Cohen (NeurIPS, 2019)

Diagnostic Curves for Black Box Models. - David I. Inouye; Liu Leqi; Joon Sik Kim; Bryon Aragam; Pradeep Ravikumar (CoRR, 2019)

Uniform Convergence of Rank-weighted Learning. - Justin Khim; Liu Leqi; Adarsh Prasad; Pradeep Ravikumar (ICML, 2020)

Automated Dependence Plots. - David I. Inouye; Liu Leqi; Joon Sik Kim; Bryon Aragam; Pradeep Ravikumar (UAI, 2020)

Off-Policy Risk Assessment in Contextual Bandits. - Audrey Huang; Liu Leqi; Zachary C. Lipton; Kamyar Azizzadenesheli (NeurIPS, 2021)

Rebounding Bandits for Modeling Satiation Effects. - Liu Leqi; Fatma Kilinç-Karzan; Zachary C. Lipton; Alan L. Montgomery (NeurIPS, 2021)

When curation becomes creation. - Liu Leqi; Dylan Hadfield-Menell; Zachary C. Lipton (Commun. ACM, 2021)

Median Optimal Treatment Regimes. - Liu Leqi; Edward H. Kennedy (CoRR, 2021)

On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk. - Audrey Huang; Liu Leqi; Zachary C. Lipton; Kamyar Azizzadenesheli (CoRR, 2021)

When Curation Becomes Creation: Algorithms, microcontent, and the vanishing distinction between platforms and creators. - Liu Leqi; Dylan Hadfield-Menell; Zachary C. Lipton (ACM Queue, 2021)

Modeling Attrition in Recommender Systems with Departing Bandits. - Omer Ben-Porat; Lee Cohen 001; Liu Leqi; Zachary C. Lipton; Yishay Mansour (AAAI, 2022)

Off-Policy Risk Assessment for Markov Decision Processes. - Audrey Huang; Liu Leqi; Zachary C. Lipton; Kamyar Azizzadenesheli (AISTATS, 2022)

Action-Sufficient State Representation Learning for Control with Structural Constraints. - Biwei Huang; Chaochao Lu; Liu Leqi; José Miguel Hernández-Lobato; Clark Glymour; Bernhard Schölkopf; Kun Zhang 001 (ICML, 2022)

Supervised Learning with General Risk Functionals. - Liu Leqi; Audrey Huang; Zachary C. Lipton; Kamyar Azizzadenesheli (ICML, 2022)

Many Ways to Be Lonely: Fine-Grained Characterization of Loneliness and Its Potential Changes in COVID-19. - Yueyi Jiang; Yunfan Jiang 001; Liu Leqi; Piotr Winkielman (ICWSM, 2022)

A Unifying Framework for Combining Complementary Strengths of Humans and ML toward Better Predictive Decision-Making. - Charvi Rastogi; Liu Leqi; Kenneth Holstein; Hoda Heidari (CoRR, 2022)

A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits. - Liu Leqi; Giulio Zhou; Fatma Kilinç-Karzan; Zachary C. Lipton; Alan L. Montgomery (CHI, 2023)

Human-Centered Machine Learning: A Statistical and Algorithmic Perspective - Leqi Liu (2023)

Personalized Language Modeling from Personalized Human Feedback. - Xinyu Li; Zachary C. Lipton; Liu Leqi (CoRR, 2024)

Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework. - Jingling Li; Zeyu Tang 002; Xiaoyu Liu; Peter Spirtes; Kun Zhang 001; Liu Leqi; Yang Liu 018 (CoRR, 2024)

Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem. - Raphael Koster; Miruna Pîslar; Andrea Tacchetti; Jan Balaguer; Leqi Liu; Romuald Elie; Oliver P. Hauser; Karl Tuyls; Matt M. Botvinick; Christopher Summerfield (CoRR, 2024)

A Unified Causal Framework for Auditing Recommender Systems for Ethical Concerns. - Vibhhu Sharma; Shantanu Gupta; Nil-Jana Akpinar; Zachary C. Lipton; Liu Leqi (CoRR, 2024)

A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement. - Hui Yuan 002; Yifan Zeng; Yue Wu; Huazheng Wang; Mengdi Wang; Liu Leqi (ICLR, 2025)

Prompting Fairness: Integrating Causality to Debias Large Language Models. - Jingling Li; Zeyu Tang 002; Xiaoyu Liu; Peter Spirtes; Kun Zhang 001; Liu Leqi; Yang Liu 018 (ICLR, 2025)

Accounting for AI and Users Shaping One Another: The Role of Mathematical Models. - Sarah Dean; Evan Dong; Meena Jagadeesan; Liu Leqi (Trans. Mach. Learn. Res., 2025)

EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations. - Haotian Zhai; Connor Lawless; Ellen Vitercik; Liu Leqi (CoRR, 2025)

More of the Same: Persistent Representational Harms Under Increased Representation. - Jennifer Mickel; Maria De-Arteaga; Leqi Liu; Kevin Tian (CoRR, 2025)

Exploring the best way for UAV visual localization under Low-altitude Multi-view Observation Condition: a Benchmark. - Yibin Ye; Xichao Teng; Shuo Chen; Zhang Li; Leqi Liu; Qifeng Yu; Tao Tan (CoRR, 2025)

Teaching with Lies: Curriculum DPO on Synthetic Negatives for Hallucination Detection. - Shrey Pandit; Ashwin Vinod; Liu Leqi; Ying Ding (CoRR, 2025)

Learning Composable Chains-of-Thought. - Fangcong Yin; Zeyu Leo Liu; Liu Leqi; Xi Ye; Greg Durrett (CoRR, 2025)

Linear Representation Transferability Hypothesis: Leveraging Small Models to Steer Large Models. - Femi Bello; Anubrata Das 001; Fanzhi Zeng; Fangcong Yin; Liu Leqi (CoRR, 2025)

AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes. - Jiahao Qiu; Xinzhe Juan; Yimin Wang; Ling Yang; Xuan Qi; Tongcheng Zhang; Jiacheng Guo; Yifu Lu; Zixin Yao; Hongru Wang 003; Shilong Liu; Xun Jiang; et al. (CoRR, 2025)

Hypothesis Testing for Quantifying LLM-Human Misalignment in Multiple Choice Settings. - Harbin Hong; Sebastian Caldas; Liu Leqi (CoRR, 2025)

ExPO: Unlocking Hard Reasoning with Self-Explanation-Guided Reinforcement Learning. - Ruiyang Zhou; Shuozhe Li; Amy Zhang; Liu Leqi (CoRR, 2025)