Robust Classification Under Sample Selection Bias. - Anqi Liu 001; Brian D. Ziebart (NIPS, 2014)

Shift-Pessimistic Active Learning Using Robust Bias-Aware Prediction. - Anqi Liu 001; Lev Reyzin; Brian D. Ziebart (AAAI, 2015)

Intent Prediction and Trajectory Forecasting via Predictive Inverse Linear-Quadratic Regulation. - Mathew Monfort; Anqi Liu 001; Brian D. Ziebart (AAAI, 2015)

Context Retrieval for Web Tables. - Hong Wang; Anqi Liu 001; Jing Wang 102; Brian D. Ziebart; Clement T. Yu; Warren Shen (ICTIR, 2015)

Robust Covariate Shift Regression. - Xiangli Chen; Mathew Monfort; Anqi Liu 001; Brian D. Ziebart (AISTATS, 2016)

Adversarial Multiclass Classification: A Risk Minimization Perspective. - Rizal Fathony; Anqi Liu 001; Kaiser Asif; Brian D. Ziebart (NIPS, 2016)

Robust Covariate Shift Prediction with General Losses and Feature Views. - Anqi Liu 001; Brian D. Ziebart (CoRR, 2017)

Kernel Robust Bias-Aware Prediction under Covariate Shift. - Anqi Liu 001; Rizal Fathony; Brian D. Ziebart (CoRR, 2017)

Consistent Robust Adversarial Prediction for General Multiclass Classification. - Rizal Fathony; Kaiser Asif; Anqi Liu 001; Mohammad Ali Bashiri; Wei Xing; Sima Behpour; Xinhua Zhang; Brian D. Ziebart (CoRR, 2018)

Regularized Learning for Domain Adaptation under Label Shifts. - Kamyar Azizzadenesheli; Anqi Liu 001; Fanny Yang; Animashree Anandkumar (ICLR (Poster), 2019)

Active Learning for Probabilistic Structured Prediction of Cuts and Matchings. - Sima Behpour; Anqi Liu 001; Brian D. Ziebart (ICML, 2019)

Finding Social Media Trolls: Dynamic Keyword Selection Methods for Rapidly-Evolving Online Debates. - Anqi Liu 001; Maya Srikanth; Nicholas Adams-Cohen; R. Michael Alvarez; Anima Anandkumar (CoRR, 2019)

Triply Robust Off-Policy Evaluation. - Anqi Liu 001; Hao Liu; Anima Anandkumar; Yisong Yue (CoRR, 2019)

Robust Regression for Safe Exploration in Control. - Anqi Liu 001; Guanya Shi; Soon-Jo Chung; Anima Anandkumar; Yisong Yue (L4DC, 2020)

Distributionally Robust Learning for Unsupervised Domain Adaptation. - Haoxuan Wang 002; Anqi Liu 001; Zhiding Yu; Yisong Yue; Anima Anandkumar (CoRR, 2020)

Robust Fairness Under Covariate Shift. - Ashkan Rezaei; Anqi Liu 001; Omid Memarrast; Brian D. Ziebart (AAAI, 2021)

Active Learning under Label Shift. - Eric Zhao 002; Anqi Liu 001; Animashree Anandkumar; Yisong Yue (AISTATS, 2021)

Dynamic Social Media Monitoring for Fast-Evolving Online Discussions. - Maya Srikanth; Anqi Liu 001; Nicholas Adams-Cohen; Jian Cao; R. Michael Alvarez; Anima Anandkumar (KDD, 2021)

Disentangling Observed Causal Effects from Latent Confounders using Method of Moments. - Anqi Liu 001; Hao Liu; Tongxin Li 001; Saeed Karimi-Bidhendi; Yisong Yue; Anima Anandkumar (CoRR, 2021)

Chance-Constrained Trajectory Optimization for Safe Exploration and Learning of Nonlinear Systems. - Yashwanth Kumar Nakka; Anqi Liu 001; Guanya Shi; Anima Anandkumar; Yisong Yue; Soon-Jo Chung (IEEE Robotics Autom. Lett., 2021)

Calibrating Zero-shot Cross-lingual (Un-)structured Predictions. - Zhengping Jiang; Anqi Liu 001; Benjamin Van Durme (EMNLP, 2022)

Ambiguous Images With Human Judgments for Robust Visual Event Classification. - Kate Sanders 002; Reno Kriz; Anqi Liu 001; Benjamin Van Durme (NeurIPS, 2022)

JAWS: Auditing Predictive Uncertainty Under Covariate Shift. - Drew Prinster; Anqi Liu 001; Suchi Saria (NeurIPS, 2022)

JAWS: Predictive Inference Under Covariate Shift. - Drew Prinster; Anqi Liu 001; Suchi Saria (CoRR, 2022)

Repeated Environment Inference for Invariant Learning. - Aayush Mishra; Anqi Liu 001 (CoRR, 2022)

Distributionally Robust Policy Gradient for Offline Contextual Bandits. - Zhouhao Yang; Yihong Guo; Pan Xu 002; Anqi Liu 001; Animashree Anandkumar (AISTATS, 2023)

Efficient Approximate Predictive Inference Under Feedback Covariate Shift with Influence Functions. - Drew Prinster; Suchi Saria; Anqi Liu 001 (COPA, 2023)

A Critical Analysis of Document Out-of-Distribution Detection. - Jiuxiang Gu; Yifei Ming; Yi Zhou; Jason Kuen; Vlad I. Morariu; Handong Zhao; Ruiyi Zhang 002; Nikolaos Barmpalios; Anqi Liu 001; Yixuan Li 001; Tong Sun 005; Ani Nenkova (EMNLP (Findings), 2023)

JAWS-X: Addressing Efficiency Bottlenecks of Conformal Prediction Under Standard and Feedback Covariate Shift. - Drew Prinster; Suchi Saria; Anqi Liu 001 (ICML, 2023)

Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach. - Haoxuan Wang 002; Zhiding Yu; Yisong Yue; Animashree Anandkumar; Anqi Liu 001; Junchi Yan (IJCAI, 2023)

Density-Softmax: Scalable and Distance-Aware Uncertainty Estimation under Distribution Shifts. - Ha Manh Bui; Anqi Liu 001 (CoRR, 2023)

MegaWika: Millions of reports and their sources across 50 diverse languages. - Samuel Barham; Orion Weller; Michelle Yuan; Kenton Murray; Mahsa Yarmohammadi; Zhengping Jiang; Siddharth Vashishtha; Alexander Martin 006; Anqi Liu 001; Aaron Steven White; Jordan L. Boyd-Graber; Benjamin Van Durme (CoRR, 2023)

RORA: Robust Free-Text Rationale Evaluation. - Zhengping Jiang; Yining Lu; Hanjie Chen; Daniel Khashabi; Benjamin Van Durme; Anqi Liu 001 (ACL (1), 2024)

Eighth Graders and a Math Intelligent Tutoring System: A Deep Neural Network Analysis. - Kelun Lu; Lingxin Hao; I-Jeng Wang; Anqi Liu 001 (AIED Companion (2), 2024)

ADOPD: A Large-Scale Document Page Decomposition Dataset. - Jiuxiang Gu; Xiangxi Shi; Jason Kuen; Lu Qi; Ruiyi Zhang 002; Anqi Liu 001; Ani Nenkova; Tong Sun 005 (ICLR, 2024)

Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them). - Drew Prinster; Samuel Don Stanton; Anqi Liu 001; Suchi Saria (ICML, 2024)

SurgicAI: A Hierarchical Platform for Fine-Grained Surgical Policy Learning and Benchmarking. - Jin Wu; Haoying Zhou; Peter Kazanzides; Adnan Munawar; Anqi Liu 001 (NeurIPS, 2024)

Responsible MLOps Design Methodology for an Auditing System for AI-Based Clinical Decision Support Systems. - Pepita Barnard; John Robert Bautista; Aidan Dakhama; Arya Farahi; Kazim Laos; Anqi Liu 001; Héctor D. Menéndez 001 (ICTSS, 2024)

Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits. - Yihong Guo; Hao Liu; Yisong Yue; Anqi Liu 001 (CoRR, 2024)

SurgicAI: A Fine-grained Platform for Data Collection and Benchmarking in Surgical Policy Learning. - Jin Wu; Haoying Zhou; Peter Kazanzides; Adnan Munawar; Anqi Liu 001 (CoRR, 2024)

Core: Robust Factual Precision Scoring with Informative Sub-Claim Identification. - Zhengping Jiang; Jingyu Zhang; Nathaniel Weir; Seth Ebner; Miriam Wanner; Kate Sanders 002; Daniel Khashabi; Anqi Liu 001; Benjamin Van Durme (CoRR, 2024)

Off-Dynamics Reinforcement Learning via Domain Adaptation and Reward Augmented Imitation. - Yihong Guo; Yixuan Wang; Yuanyuan Shi; Pan Xu 002; Anqi Liu 001 (CoRR, 2024)

Designing for Appropriate Reliance: The Roles of AI Uncertainty Presentation, Initial User Decision, and User Demographics in AI-Assisted Decision-Making. - Shiye Cao; Anqi Liu 001; Chien-Ming Huang 001 (Proc. ACM Hum. Comput. Interact., 2024)

Addressing the Binning Problem in Calibration Assessment through Scalar Annotations. - Zhengping Jiang; Anqi Liu 001; Benjamin Van Durme (Trans. Assoc. Comput. Linguistics, 2024)

Towards Human-Compatible Autonomous Car: A Study of Non-Verbal Turing Test in Automated Driving With Affective Transition Modelling. - Zhaoning Li; Qiaoli Jiang; Zhengming Wu; Anqi Liu 001; Haiyan Wu; Miner Huang; Kai Huang 001; Yixuan Ku (IEEE Trans. Affect. Comput., 2024)

Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift. - Gina Wong; Joshua Gleason; Rama Chellappa; Yoav Wald; Anqi Liu 001 (Trans. Mach. Learn. Res., 2024)

Core: Robust Factual Precision with Informative Sub-Claim Identification. - Zhengping Jiang; Jingyu Zhang; Nathaniel Weir; Seth Ebner; Miriam Wanner; Kate Sanders 002; Daniel Khashabi; Anqi Liu 001; Benjamin Van Durme (ACL (Findings), 2025)

Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits. - Ha Manh Bui; Enrique Mallada; Anqi Liu 001 (AISTATS, 2025)

WATCH: Adaptive Monitoring for AI Deployments via Weighted-Conformal Martingales. - Drew Prinster; Xing Han; Anqi Liu 001; Suchi Saria (ICML, 2025)

Conformal Linguistic Calibration: Trading-off between Factuality and Specificity. - Zhengping Jiang; Anqi Liu 001; Benjamin Van Durme (NeurIPS, 2025)

Interruption Handling for Conversational Robots. - Shiye Cao; Jiwon Moon 002; Amama Mahmood; Victor Nikhil Antony; Ziang Xiao; Anqi Liu 001; Chien-Ming Huang 001 (CoRR, 2025)

Training-Aware Risk Control for Intensity Modulated Radiation Therapies Quality Assurance with Conformal Prediction. - Kevin He; David Adam; Sarah Han-Oh; Anqi Liu 001 (CoRR, 2025)

On the challenges of detecting MCI using EEG in the wild. - Aayush Mishra; David Joffe; Sankara Surendra Telidevara; David S. Oakley; Anqi Liu 001 (CoRR, 2025)

ICL CIPHERS: Quantifying "Learning" in In-Context Learning via Substitution Ciphers. - Zhouxiang Fang; Aayush Mishra; Muhan Gao; Anqi Liu 001; Daniel Khashabi (CoRR, 2025)

Always Tell Me The Odds: Fine-grained Conditional Probability Estimation. - Liaoyaqi Wang; Zhengping Jiang; Anqi Liu 001; Benjamin Van Durme (CoRR, 2025)

Improving Coverage in Combined Prediction Sets with Weighted p-values. - Gina Wong; Drew Prinster; Suchi Saria; Rama Chellappa; Anqi Liu 001 (CoRR, 2025)

MOBODY: Model Based Off-Dynamics Offline Reinforcement Learning. - Yihong Guo; Yu Yang 019; Pan Xu 002; Anqi Liu 001 (CoRR, 2025)

Do Students Rely on AI? Analysis of Student-ChatGPT Conversations from a Field Study. - Jiayu Zheng; Lingxin Hao; Kelun Lu; Ashi Garg; Mike Reese; Melo-Jean Yap; I-Jeng Wang; Xingyun Wu; Wenrui Huang; Jenna Hoffman; Ariane Kelly; My Le; et al. (CoRR, 2025)

IA2: Alignment with ICL Activations Improves Supervised Fine-Tuning. - Aayush Mishra; Daniel Khashabi; Anqi Liu 001 (CoRR, 2025)

PAME-AI: Patient Messaging Creation and Optimization using Agentic AI. - Junjie Luo 012; Yihong Guo; Anqi Liu 001; Ritu Agarwal; Guodong Gordon Gao (CoRR, 2025)

Calibrated Uncertainty Sampling for Active Learning. - Ha Manh Bui; Iliana Maifeld-Carucci; Anqi Liu 001 (CoRR, 2025)

Q-Learning with Shift-Aware Upper Confidence Bound in Non-Stationary Reinforcement Learning. - Ha Manh Bui; Felix Parker; Kimia Ghobadi; Anqi Liu 001 (CoRR, 2025)

Group-Sensitive Offline Contextual Bandits. - Yihong Guo; Junjie Luo 012; Gordon Gao 001; Ritu Agarwal; Anqi Liu 001 (CoRR, 2025)

Analyzing Political Text at Scale with Online Tensor LDA. - Sara Kangaslahti; Danny Ebanks; Jean Kossaifi; Anqi Liu 001; R. Michael Alvarez; Animashree Anandkumar (CoRR, 2025)

Genomic Next-Token Predictors are In-Context Learners. - Nathan Breslow; Aayush Mishra; Mahler Revsine; Michael C. Schatz; Anqi Liu 001; Daniel Khashabi (CoRR, 2025)

OIDA-QA: A Multimodal Benchmark for Analyzing the Opioid Industry Documents Archive. - Xuan Shen; Brian Wingenroth; Zichao Wang 001; Jason Kuen; Wanrong Zhu; Ruiyi Zhang 002; Yiwei Wang; Lichun Ma; Anqi Liu 001; Hongfu Liu; Tong Sun 005; Kevin S. Hawkins; et al. (AAAI, 2026)

Reframing Conversational Design in HRI: Deliberate Design with AI Scaffolds. - Shiye Cao; Jiwon Moon 002; Yifan Xu 031; Anqi Liu 001; Chien-Ming Huang 001 (HRI, 2026)

Conformal Policy Control. - Drew Prinster; Clara Fannjiang; Ji Won Park; Kyunghyun Cho; Anqi Liu 001; Suchi Saria; Samuel Stanton (CoRR, 2026)

Steered LLM Activations are Non-Surjective. - Aayush Mishra; Daniel Khashabi; Anqi Liu 001 (CoRR, 2026)

Process Supervision of Confidence Margin for Calibrated LLM Reasoning. - Liaoyaqi Wang; Chunsheng Zuo; William Jurayj; Benjamin Van Durme; Anqi Liu 001 (CoRR, 2026)

Cross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning. - Yu Yang 019; Yihong Guo; Anqi Liu 001; Pan Xu 002 (CoRR, 2026)

Configurable Reward Model for Balanced Safety Alignment. - Zhengping Jiang; Mehran Khodabandeh; Akash Bharadwaj; Manik Bhandari; Mayur Srungarapu; Anqi Liu 001; Benjamin Van Durme; Li Chen (CoRR, 2026)