Liu Leqi

According to our database, Liu Leqi authored at least 39 papers between 2015 and 2025.

Collaborative distances:

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

2025

ExPO: Unlocking Hard Reasoning with Self-Explanation-Guided Reinforcement Learning.

Ruiyang Zhou, Shuozhe Li, Amy Zhang, Liu Leqi

CoRR, July, 2025

Hypothesis Testing for Quantifying LLM-Human Misalignment in Multiple Choice Settings.

Harbin Hong, Sebastian Caldas, Liu Leqi

CoRR, June, 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, Shilong Liu, Xun Jiang, Liu Leqi, Mengdi Wang

CoRR, June, 2025

Linear Representation Transferability Hypothesis: Leveraging Small Models to Steer Large Models.

Femi Bello, Anubrata Das, Fanzhi Zeng, Fangcong Yin, Liu Leqi

CoRR, June, 2025

Learning Composable Chains-of-Thought.

Fangcong Yin, Zeyu Leo Liu, Liu Leqi, Xi Ye, Greg Durrett

CoRR, May, 2025

Teaching with Lies: Curriculum DPO on Synthetic Negatives for Hallucination Detection.

Shrey Pandit, Ashwin Vinod, Liu Leqi, Ying Ding

CoRR, May, 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, March, 2025

More of the Same: Persistent Representational Harms Under Increased Representation.

Jennifer Mickel, Maria De-Arteaga, Leqi Liu, Kevin Tian

CoRR, March, 2025

EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations.

Haotian Zhai, Connor Lawless, Ellen Vitercik, Liu Leqi

CoRR, February, 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

Prompting Fairness: Integrating Causality to Debias Large Language Models.

Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement.

Hui Yuan, Yifan Zeng, Yue Wu, Huazheng Wang, Mengdi Wang, Liu Leqi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

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

Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework.

Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu

CoRR, 2024

Personalized Language Modeling from Personalized Human Feedback.

Xinyu Li, Zachary C. Lipton, Liu Leqi

CoRR, 2024

2023

Human-Centered Machine Learning: A Statistical and Algorithmic Perspective

Leqi Liu

PhD thesis, 2023

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

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

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

Many Ways to Be Lonely: Fine-Grained Characterization of Loneliness and Its Potential Changes in COVID-19.

Yueyi Jiang, Yunfan Jiang, Liu Leqi, Piotr Winkielman

Proceedings of the Sixteenth International AAAI Conference on Web and Social Media, 2022

Supervised Learning with General Risk Functionals.

Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli

Proceedings of the International Conference on Machine Learning, 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

Proceedings of the International Conference on Machine Learning, 2022

Off-Policy Risk Assessment for Markov Decision Processes.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Modeling Attrition in Recommender Systems with Departing Bandits.

Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

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

On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

CoRR, 2021

Median Optimal Treatment Regimes.

Liu Leqi, Edward H. Kennedy

CoRR, 2021

When curation becomes creation.

Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton

Commun. ACM, 2021

Rebounding Bandits for Modeling Satiation Effects.

Liu Leqi, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery

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

Off-Policy Risk Assessment in Contextual Bandits.

Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli

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

2020

Automated Dependence Plots.

David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

Uniform Convergence of Rank-weighted Learning.

Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Diagnostic Curves for Black Box Models.

David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar

CoRR, 2019

Game Design for Eliciting Distinguishable Behavior.

Fan Yang, Liu Leqi, Yifan Wu, Zachary Chase Lipton, Pradeep Ravikumar, Tom M. Mitchell, William W. Cohen

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

On Human-Aligned Risk Minimization.

Liu Leqi, Adarsh Prasad, Pradeep Ravikumar

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

2018

Sample Complexity of Nonparametric Semi-Supervised Learning.

Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

CoRR, 2018

The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models.

Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Analyzing Personality through Social Media Profile Picture Choice.

Leqi Liu, Daniel Preotiuc-Pietro, Zahra Riahi Samani, Mohsen Ebrahimi Moghaddam, Lyle H. Ungar

Proceedings of the Tenth International Conference on Web and Social Media, 2016

2015

Shared genetic architecture in autoimmune disease - preliminary analysis.

Leqi Liu, Jia Tao, Ziyan Yang, Fadi Towfic

Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015