Liu Leqi - RankMe

51 papers A* 13A 3Journal 34Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Evaluating Stochasticity in Deep Research Agents. CoRR Haotian Zhai, Elias Stengel-Eskin, Pratik Patil, Liu Leqi
2026	J	`jnl`	Learning Robust Reasoning through Guided Adversarial Self-Play. CoRR Shuozhe Li, Vaishnav Tadiparthi, Kwonjoon Lee, Nakul Agarwal, Hossein Nourkhiz Mahjoub, Ehsan Moradi-Pari, Lizhang Chen, Amy Zhang, Liu Leqi
2025	A*	`conf`	A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement. ICLR Hui Yuan, Yifan Zeng, Yue Wu, Huazheng Wang, Mengdi Wang, Liu Leqi
2025	J	`jnl`	Accounting for AI and Users Shaping One Another: The Role of Mathematical Models. Trans. Mach. Learn. Res. Sarah Dean, Evan Dong, Meena Jagadeesan, Liu Leqi
2025	J	`jnl`	AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes. CoRR 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
2025	A*	`conf`	EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations. ICML Haotian Zhai, Connor Lawless, Ellen Vitercik, Liu Leqi
2025	J	`jnl`	EquivaMap: Leveraging LLMs for Automatic Equivalence Checking of Optimization Formulations. CoRR Haotian Zhai, Connor Lawless, Ellen Vitercik, Liu Leqi
2025	J	`jnl`	ExPO: Unlocking Hard Reasoning with Self-Explanation-Guided Reinforcement Learning. CoRR Ruiyang Zhou, Shuozhe Li, Amy Zhang, Liu Leqi
2025	J	`jnl`	Hypothesis Testing for Quantifying LLM-Human Misalignment in Multiple Choice Settings. CoRR Harbin Hong, Sebastian Caldas, Liu Leqi
2025	J	`jnl`	Learning Composable Chains-of-Thought. CoRR Fangcong Yin, Zeyu Leo Liu, Liu Leqi, Xi Ye, Greg Durrett
2025	J	`jnl`	Linear Representation Transferability Hypothesis: Leveraging Small Models to Steer Large Models. CoRR Femi Bello, Anubrata Das, Fanzhi Zeng, Fangcong Yin, Liu Leqi
2025	J	`jnl`	Position: Thematic Analysis of Unstructured Clinical Transcripts with Large Language Models. CoRR Seungjun Yi, Joakim Nguyen, Terence Lim, Andrew Well, Joseph Skrovan, Mehak Beri, YongGeon Lee, Kavita Radhakrishnan, Liu Leqi, Mia K. Markey, Ying Ding
2025	A*	`conf`	Prompting Fairness: Integrating Causality to Debias Large Language Models. ICLR Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
2025	J	`jnl`	SFT-TA: Supervised Fine-Tuned Agents in Multi-Agent LLMs for Automated Inductive Thematic Analysis. CoRR Seungjun Yi, Joakim Nguyen, Huimin Xu, Terence Lim, Joseph Skrovan, Mehak Beri, Hitakshi Modi, Andrew Well, Liu Leqi, Mia K. Markey, Ying Ding
2025	J	`jnl`	Teaching with Lies: Curriculum DPO on Synthetic Negatives for Hallucination Detection. CoRR Shrey Pandit, Ashwin Vinod, Liu Leqi, Ying Ding
2025	—	`conf`	The Progress Illusion: Revisiting meta-evaluation standards of LLM evaluators. EMNLP (Findings) Tianruo Rose Xu, Vedant Gaur, Liu Leqi, Tanya Goyal
2024	J	`jnl`	A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement. CoRR Hui Yuan, Yifan Zeng, Yue Wu, Huazheng Wang, Mengdi Wang, Liu Leqi
2024	J	`jnl`	A Unified Causal Framework for Auditing Recommender Systems for Ethical Concerns. CoRR Vibhhu Sharma, Shantanu Gupta, Nil-Jana Akpinar, Zachary C. Lipton, Liu Leqi
2024	J	`jnl`	Accounting for AI and Users Shaping One Another: The Role of Mathematical Models. CoRR Sarah Dean, Evan Dong, Meena Jagadeesan, Liu Leqi
2024	J	`jnl`	Personalized Language Modeling from Personalized Human Feedback. CoRR Xinyu Li, Zachary C. Lipton, Liu Leqi
2024	J	`jnl`	Steering LLMs Towards Unbiased Responses: A Causality-Guided Debiasing Framework. CoRR Jingling Li, Zeyu Tang, Xiaoyu Liu, Peter Spirtes, Kun Zhang, Liu Leqi, Yang Liu
2023	A*	`conf`	A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits. CHI Liu Leqi, Giulio Zhou, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery
2023	J	`jnl`	A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits. CoRR Liu Leqi, Giulio Zhou, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery
2022	J	`jnl`	A Unifying Framework for Combining Complementary Strengths of Humans and ML toward Better Predictive Decision-Making. CoRR Charvi Rastogi, Liu Leqi, Kenneth Holstein, Hoda Heidari
2022	A*	`conf`	Action-Sufficient State Representation Learning for Control with Structural Constraints. ICML Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
2022	A	`conf`	Many Ways to Be Lonely: Fine-Grained Characterization of Loneliness and Its Potential Changes in COVID-19. ICWSM Yueyi Jiang, Yunfan Jiang, Liu Leqi, Piotr Winkielman
2022	J	`jnl`	Many Ways to be Lonely: Fine-grained Characterization of Loneliness and its Potential Changes in COVID-19. CoRR Yueyi Jiang, Yunfan Jiang, Liu Leqi, Piotr Winkielman
2022	A*	`conf`	Modeling Attrition in Recommender Systems with Departing Bandits. AAAI Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour
2022	J	`jnl`	Modeling Attrition in Recommender Systems with Departing Bandits. CoRR Omer Ben-Porat, Lee Cohen, Liu Leqi, Zachary C. Lipton, Yishay Mansour
2022	A	`conf`	Off-Policy Risk Assessment for Markov Decision Processes. AISTATS Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2022	J	`jnl`	Off-Policy Risk Assessment in Markov Decision Processes. CoRR Audrey Huang, Liu Leqi, Zachary Chase Lipton, Kamyar Azizzadenesheli
2022	A*	`conf`	Supervised Learning with General Risk Functionals. ICML Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli
2022	J	`jnl`	Supervised Learning with General Risk Functionals. CoRR Liu Leqi, Audrey Huang, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	Action-Sufficient State Representation Learning for Control with Structural Constraints. CoRR Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
2021	J	`jnl`	Median Optimal Treatment Regimes. CoRR Liu Leqi, Edward H. Kennedy
2021	A*	`conf`	Off-Policy Risk Assessment in Contextual Bandits. NeurIPS Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	Off-Policy Risk Assessment in Contextual Bandits. CoRR Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	J	`jnl`	On the Convergence and Optimality of Policy Gradient for Markov Coherent Risk. CoRR Audrey Huang, Liu Leqi, Zachary C. Lipton, Kamyar Azizzadenesheli
2021	A*	`conf`	Rebounding Bandits for Modeling Satiation Effects. NeurIPS Liu Leqi, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery
2021	J	`jnl`	When Curation Becomes Creation: Algorithms, Microcontent, and the Vanishing Distinction between Platforms and Creators. CoRR Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton
2021	J	`jnl`	When Curation Becomes Creation: Algorithms, microcontent, and the vanishing distinction between platforms and creators. ACM Queue Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton
2021	J	`jnl`	When curation becomes creation. Commun. ACM Liu Leqi, Dylan Hadfield-Menell, Zachary C. Lipton
2020	A	`conf`	Automated Dependence Plots. UAI David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar
2020	J	`jnl`	Rebounding Bandits for Modeling Satiation Effects. CoRR Liu Leqi, Fatma Kilinç-Karzan, Zachary C. Lipton, Alan L. Montgomery
2020	A*	`conf`	Uniform Convergence of Rank-weighted Learning. ICML Justin Khim, Liu Leqi, Adarsh Prasad, Pradeep Ravikumar
2019	J	`jnl`	Diagnostic Curves for Black Box Models. CoRR David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar
2019	A*	`conf`	Game Design for Eliciting Distinguishable Behavior. NeurIPS Fan Yang, Liu Leqi, Yifan Wu, Zachary Chase Lipton, Pradeep Ravikumar, Tom M. Mitchell, William W. Cohen
2019	J	`jnl`	Game Design for Eliciting Distinguishable Behavior. CoRR Fan Yang, Liu Leqi, Yifan Wu, Zachary C. Lipton, Pradeep Ravikumar, William W. Cohen, Tom M. Mitchell
2019	A*	`conf`	On Human-Aligned Risk Minimization. NeurIPS Liu Leqi, Adarsh Prasad, Pradeep Ravikumar
2018	J	`jnl`	Sample Complexity of Nonparametric Semi-Supervised Learning. CoRR Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing
2018	A*	`conf`	The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models. NeurIPS Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing