MiPPS: A Generative Model for Multi-Manifold Clustering. - Oluwasanmi Koyejo; Joydeep Ghosh (AAAI Fall Symposium: Manifold Learning and Its Applications, 2009)

Organizing Committee. - Oluwasanmi Koyejo; Richard Souvenir (AAAI Fall Symposium: Manifold Learning and Its Applications, 2010)

Preface: Manifold Learning and Its Applications. - Oluwasanmi Koyejo; Richard Souvenir (AAAI Fall Symposium: Manifold Learning and Its Applications, 2010)

Reports of the AAAI 2009 Fall Symposia. - Roger Azevedo; Trevor J. M. Bench-Capon; Gautam Biswas; Ted Carmichael; Nancy L. Green; Mirsad Hadzikadic; Oluwasanmi Koyejo; Unmesh Kurup; Simon Parsons; Roberto Pirrone; Henry Prakken; Alexei V. Samsonovich; et al. (AI Mag., 2010)

A kernel-based approach to exploiting interaction-networks in heterogeneous information sources for improved recommender systems. - Oluwasanmi Koyejo; Joydeep Ghosh (HetRec@RecSys, 2011)

Reports of the AAAI 2010 Fall Symposia. - Roger Azevedo; Gautam Biswas; Dan Bohus; Ted Carmichael; Mark A. Finlayson; Mirsad Hadzikadic; Catherine Havasi; Eric Horvitz; Takayuki Kanda 001; Oluwasanmi Koyejo; William F. Lawless; Douglas B. Lenat; et al. (AI Mag., 2011)

Learning to Rank With Bregman Divergences and Monotone Retargeting. - Sreangsu Acharyya; Oluwasanmi Koyejo; Joydeep Ghosh (UAI, 2012)

Bayesian Structure Learning for Functional Neuroimaging. - Mijung Park; Oluwasanmi Koyejo; Joydeep Ghosh; Russell A. Poldrack; Jonathan W. Pillow (AISTATS, 2013)

Identifying candidate disease genes using a trace norm constrained bipartite raking model. - Cheng H. Lee; Oluwasanmi Koyejo; Joydeep Ghosh (EMBC, 2013)

Constrained Gaussian Process Regression for Gene-Disease Association. - Oluwasanmi Koyejo; Cheng H. Lee; Joydeep Ghosh (ICDM Workshops, 2013)

Learning Predictive Cognitive Structure from fMRI Using Supervised Topic Models. - Oluwasanmi Koyejo; Priyank Patel; Joydeep Ghosh; Russell A. Poldrack (PRNI, 2013)

Retargeted matrix factorization for collaborative filtering. - Oluwasanmi Koyejo; Sreangsu Acharyya; Joydeep Ghosh (RecSys, 2013)

Constrained Bayesian Inference for Low Rank Multitask Learning. - Oluwasanmi Koyejo; Joydeep Ghosh (UAI, 2013)

The trace norm constrained matrix-variate Gaussian process for multitask bipartite ranking - Oluwasanmi Koyejo; Cheng H. Lee; Joydeep Ghosh (CoRR, 2013)

Toward open sharing of task-based fMRI data: the OpenfMRI project. - Russell A. Poldrack; Deanna M. Barch; Jason P. Mitchell; Tor D. Wager; Anthony D. Wagner; Joseph T. Devlin; Chad Cumba; Oluwasanmi Koyejo; Michael P. Milham (Frontiers Neuroinformatics, 2013)

On Prior Distributions and Approximate Inference for Structured Variables. - Oluwasanmi Koyejo; Rajiv Khanna; Joydeep Ghosh; Russell A. Poldrack (NIPS, 2014)

Consistent Binary Classification with Generalized Performance Metrics. - Oluwasanmi Koyejo; Nagarajan Natarajan; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2014)

Sparse Bayesian structure learning with dependent relevance determination priors. - Anqi Wu; Mijung Park; Oluwasanmi Koyejo; Jonathan W. Pillow (NIPS, 2014)

A constrained matrix-variate Gaussian process for transposable data. - Oluwasanmi Koyejo; Cheng H. Lee; Joydeep Ghosh (Mach. Learn., 2014)

Generalized Linear Models for Aggregated Data. - Avradeep Bhowmik; Joydeep Ghosh; Oluwasanmi Koyejo (AISTATS, 2015)

Sparse Submodular Probabilistic PCA. - Rajiv Khanna; Joydeep Ghosh; Russell A. Poldrack; Oluwasanmi Koyejo (AISTATS, 2015)

Simultaneous Prognosis of Multiple Chronic Conditions from Heterogeneous EHR Data. - Shalmali Joshi; Oluwasanmi Koyejo; Joydeep Ghosh (ICHI, 2015)

Simultaneous Prognosis and Exploratory Analysis of Multiple Chronic Conditions Using Clinical Notes. - Shalmali Joshi; Oluwasanmi Koyejo; Kristine Resurreccion; Joydeep Ghosh (ICHI, 2015)

Consistent Multilabel Classification. - Oluwasanmi Koyejo; Nagarajan Natarajan; Pradeep Ravikumar; Inderjit S. Dhillon (NIPS, 2015)

Optimal Decision-Theoretic Classification Using Non-Decomposable Performance Metrics. - Nagarajan Natarajan; Oluwasanmi Koyejo; Pradeep Ravikumar; Inderjit S. Dhillon (CoRR, 2015)

Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives. - James M. Shine; Oluwasanmi Koyejo; Peter T. Bell; Krzysztof J. Gorgolewski; Moran Gilat; Russell A. Poldrack (NeuroImage, 2015)

A Simple and Provable Algorithm for Sparse Diagonal CCA. - Megasthenis Asteris; Anastasios Kyrillidis; Oluwasanmi Koyejo; Russell A. Poldrack (ICML, 2016)

Sparse Parameter Recovery from Aggregated Data. - Avradeep Bhowmik; Joydeep Ghosh; Oluwasanmi Koyejo (ICML, 2016)

Optimal Classification with Multivariate Losses. - Nagarajan Natarajan; Oluwasanmi Koyejo; Pradeep Ravikumar; Inderjit S. Dhillon (ICML, 2016)

Preference Completion from Partial Rankings. - Suriya Gunasekar; Oluwasanmi Koyejo; Joydeep Ghosh (NIPS, 2016)

Examples are not enough, learn to criticize! Criticism for Interpretability. - Been Kim; Oluwasanmi Koyejo; Rajiv Khanna (NIPS, 2016)

Generalized Correspondence-LDA Models (GC-LDA) for Identifying Functional Regions in the Brain. - Timothy N. Rubin; Oluwasanmi Koyejo; Michael N. Jones; Tal Yarkoni (NIPS, 2016)

Rényi divergence minimization based co-regularized multiview clustering. - Shalmali Joshi; Joydeep Ghosh; Mark Reid; Oluwasanmi Koyejo (Mach. Learn., 2016)

Frequency Domain Predictive Modelling with Aggregated Data. - Avradeep Bhowmik; Joydeep Ghosh; Oluwasanmi Koyejo (AISTATS, 2017)

Information Projection and Approximate Inference for Structured Sparse Variables. - Rajiv Khanna; Joydeep Ghosh; Russell A. Poldrack; Oluwasanmi Koyejo (AISTATS, 2017)

Consistency Analysis for Binary Classification Revisited. - Krzysztof Dembczynski; Wojciech Kotlowski; Oluwasanmi Koyejo; Nagarajan Natarajan (ICML, 2017)

A Deflation Method for Structured Probabilistic PCA. - Rajiv Khanna; Joydeep Ghosh; Russell A. Poldrack; Oluwasanmi Koyejo (SDM, 2017)

What's in a pattern? Examining the type of signal multivariate analysis uncovers at the group level. - Ro'ee Gilron; Jonathan D. Rosenblatt; Oluwasanmi Koyejo; Russell A. Poldrack; Roy Mukamel (NeuroImage, 2017)

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition. - Timothy N. Rubin; Oluwasanmi Koyejo; Krzysztof J. Gorgolewski; Michael N. Jones; Russell A. Poldrack; Tal Yarkoni (PLoS Comput. Biol., 2017)

Bayesian Structure Learning for Dynamic Brain Connectivity. - Michael Riis Andersen; Ole Winther; Lars Kai Hansen; Russell A. Poldrack; Oluwasanmi Koyejo (AISTATS, 2018)

Binary Classification with Karmic, Threshold-Quasi-Concave Metrics. - Bowei Yan; Oluwasanmi Koyejo; Kai Zhong; Pradeep Ravikumar (ICML, 2018)

Clustered Fused Graphical Lasso. - Yizhi Zhu; Oluwasanmi Koyejo (UAI, 2018)

Generalized Byzantine-tolerant SGD. - Cong Xie; Oluwasanmi Koyejo; Indranil Gupta (CoRR, 2018)

Learning the Base Distribution in Implicit Generative Models. - Y. Cem Sübakan; Oluwasanmi Koyejo; Paris Smaragdis (CoRR, 2018)

Phocas: dimensional Byzantine-resilient stochastic gradient descent. - Cong Xie; Oluwasanmi Koyejo; Indranil Gupta (CoRR, 2018)

Zeno: Byzantine-suspicious stochastic gradient descent. - Cong Xie; Oluwasanmi Koyejo; Indranil Gupta (CoRR, 2018)

Eliciting Binary Performance Metrics. - Gaurush Hiranandani; Shant Boodaghians; Ruta Mehta; Oluwasanmi Koyejo (CoRR, 2018)

xGEMs: Generating Examplars to Explain Black-Box Models. - Shalmali Joshi; Oluwasanmi Koyejo; Been Kim; Joydeep Ghosh (CoRR, 2018)

A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials. - Yogatheesan Varatharajah; Brent M. Berry; Sanmi Koyejo; Ravishankar K. Iyer (CoRR, 2018)

Synthetic Power Analyses: Empirical Evaluation and Application to Cognitive Neuroimaging. - Peiye Zhuang; Bliss Chapman; Ran Li; Sanmi Koyejo (ACSSC, 2019)

Performance Metric Elicitation from Pairwise Classifier Comparisons. - Gaurush Hiranandani; Shant Boodaghians; Ruta Mehta; Oluwasanmi Koyejo (AISTATS, 2019)

Interpreting Black Box Predictions using Fisher Kernels. - Rajiv Khanna; Been Kim; Joydeep Ghosh; Sanmi Koyejo (AISTATS, 2019)

Max-Sliced Wasserstein Distance and Its Use for GANs. - Ishan Deshpande; Yuan-Ting Hu; Ruoyu Sun 001; Ayis Pyrros; Nasir Siddiqui; Sanmi Koyejo; Zhizhen Zhao 001; David A. Forsyth; Alexander G. Schwing (CVPR, 2019)

Partially Linear Additive Gaussian Graphical Models. - Sinong Geng; Minhao Yan; Mladen Kolar; Sanmi Koyejo (ICML, 2019)

Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance. - Cong Xie; Sanmi Koyejo; Indranil Gupta (ICML, 2019)

FMRI Data Augmentation Via Synthesis. - Peiye Zhuang; Alexander G. Schwing; Oluwasanmi Koyejo (ISBI, 2019)

Multiclass Performance Metric Elicitation. - Gaurush Hiranandani; Shant Boodaghians; Ruta Mehta; Oluwasanmi Koyejo (NeurIPS, 2019)

Learning Sparse Distributions using Iterative Hard Thresholding. - Jacky Y. Zhang; Rajiv Khanna; Anastasios Kyrillidis; Oluwasanmi Koyejo (NeurIPS, 2019)

SLSGD: Secure and Efficient Distributed On-device Machine Learning. - Cong Xie; Oluwasanmi Koyejo; Indranil Gupta (ECML/PKDD (2), 2019)

Joint Nonparametric Precision Matrix Estimation with Confounding. - Sinong Geng; Mladen Kolar; Oluwasanmi Koyejo (UAI, 2019)

Fall of Empires: Breaking Byzantine-tolerant SGD by Inner Product Manipulation. - Cong Xie; Oluwasanmi Koyejo; Indranil Gupta (UAI, 2019)

Clustered Monotone Transforms for Rating Factorization. - Gaurush Hiranandani; Raghav Somani; Oluwasanmi Koyejo; Sreangsu Acharyya (WSDM, 2019)

Asynchronous Federated Optimization. - Cong Xie; Sanmi Koyejo; Indranil Gupta (CoRR, 2019)

Practical Distributed Learning: Secure Machine Learning with Communication-Efficient Local Updates. - Cong Xie; Sanmi Koyejo; Indranil Gupta (CoRR, 2019)

Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems. - Shalmali Joshi; Oluwasanmi Koyejo; Warut Vijitbenjaronk; Been Kim; Joydeep Ghosh (CoRR, 2019)

Consistent Classification with Generalized Metrics. - Xiaoyan Wang; Ran Li; Bowei Yan; Oluwasanmi Koyejo (CoRR, 2019)

Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates. - Cong Xie; Oluwasanmi Koyejo; Indranil Gupta; Haibin Lin (CoRR, 2019)

Advances and Open Problems in Federated Learning. - Peter Kairouz; H. Brendan McMahan; Brendan Avent; Aurélien Bellet; Mehdi Bennis; Arjun Nitin Bhagoji; Kallista A. Bonawitz; Zachary Charles; Graham Cormode; Rachel Cummings; Rafael G. L. D'Oliveira; Salim El Rouayheb; et al. (CoRR, 2019)

Learning Controllable Disentangled Representations with Decorrelation Regularization. - Zengjie Song; Oluwasanmi Koyejo; Jiangshe Zhang 001 (CoRR, 2019)

Dependent relevance determination for smooth and structured sparse regression. - Anqi Wu; Oluwasanmi Koyejo; Jonathan W. Pillow (J. Mach. Learn. Res., 2019)

Some New Tricks for Deep Glioma Segmentation. - Chase Duncan; Francis Roxas; Neel Jani; Jane Maksimovic; Matthew T. Bramlet; Brad Sutton; Sanmi Koyejo (BrainLes@MICCAI (2), 2020)

Towards a Deep Network Architecture for Structured Smoothness. - Haroun Habeeb; Oluwasanmi Koyejo (ICLR, 2020)

Optimization and Analysis of the pAp@k Metric for Recommender Systems. - Gaurush Hiranandani; Warut Vijitbenjaronk; Sanmi Koyejo; Prateek Jain (ICML, 2020)

Zeno++: Robust Fully Asynchronous SGD. - Cong Xie; Sanmi Koyejo; Indranil Gupta (ICML, 2020)

On the consistency of top-k surrogate losses. - Forest Yang; Sanmi Koyejo (ICML, 2020)

A Generative Modeling Approach for Interpreting Population-Level Variability in Brain Structure. - Ran Liu; Cem Subakan; Aishwarya H. Balwani; Jennifer D. Whitesell; Julie Harris 002; Sanmi Koyejo; Eva L. Dyer (MICCAI (5), 2020)

Fair Performance Metric Elicitation. - Gaurush Hiranandani; Harikrishna Narasimhan; Oluwasanmi Koyejo (NeurIPS, 2020)

CSER: Communication-efficient SGD with Error Reset. - Cong Xie; Shuai Zheng 004; Oluwasanmi Koyejo; Indranil Gupta; Mu Li 003; Haibin Lin (NeurIPS, 2020)

Fairness with Overlapping Groups; a Probabilistic Perspective. - Forest Yang; Mouhamadou Cisse; Oluwasanmi Koyejo (NeurIPS, 2020)

Detecting evolutionary patterns of cancers using consensus trees. - Sarah A. Christensen; Juho Kim; Nicholas Chia; Oluwasanmi Koyejo; Mohammed El-Kebir (Bioinform., 2020)

Towards A Controllable Disentanglement Network. - Zengjie Song; Oluwasanmi Koyejo; Jiangshe Zhang 001 (CoRR, 2020)

Rich-Item Recommendations for Rich-Users via GCNN: Exploiting Dynamic and Static Side Information. - Amar Budhiraja; Gaurush Hiranandani; Navya Yarrabelly; Ayush Choure; Oluwasanmi Koyejo; Prateek Jain (CoRR, 2020)

Fairness with Overlapping Groups. - Forest Yang; Moustapha Cissé; Sanmi Koyejo (CoRR, 2020)

Does Adversarial Transferability Indicate Knowledge Transferability? - Kaizhao Liang; Jacky Y. Zhang; Oluwasanmi Koyejo; Bo Li 026 (CoRR, 2020)

Bayesian Coresets: An Optimization Perspective. - Jacky Y. Zhang; Rajiv Khanna; Anastasios Kyrillidis; Oluwasanmi Koyejo (CoRR, 2020)

Quadratic Metric Elicitation with Application to Fairness. - Gaurush Hiranandani; Jatin Mathur; Harikrishna Narasimhan; Oluwasanmi Koyejo (CoRR, 2020)

Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective. - Jacky Zhang; Rajiv Khanna; Anastasios Kyrillidis; Sanmi Koyejo (AISTATS, 2021)

Enjoy Your Editing: Controllable GANs for Image Editing via Latent Space Navigation. - Peiye Zhuang; Oluwasanmi Koyejo; Alexander G. Schwing (ICLR, 2021)

Optimizing Black-box Metrics with Iterative Example Weighting. - Gaurush Hiranandani; Jatin Mathur; Harikrishna Narasimhan; Mahdi Milani Fard; Sanmi Koyejo (ICML, 2021)

Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability. - Kaizhao Liang; Jacky Y. Zhang; Boxin Wang; Zhuolin Yang; Sanmi Koyejo; Bo Li 026 (ICML, 2021)

Learning To Recover Sharp Detail From Simulated Low-Dose Ct Studies. - Patrick Cole; Ayis Pyrros; Oluwasanmi Koyejo (ISBI, 2021)

Labeling Cost Sensitive Batch Active Learning For Brain Tumor Segmentation. - Maohao Shen; Jacky Y. Zhang; Leihao Chen; Weiman Yan; Neel Jani; Brad Sutton; Oluwasanmi Koyejo (ISBI, 2021)

Nonlinear reconfiguration of network edges, topology and information content during an artificial learning task. - James M. Shine; Mike Li; Oluwasanmi Koyejo; Ben D. Fulcher; Joseph T. Lizier (Brain Informatics, 2021)

A Field Guide to Federated Optimization. - Jianyu Wang; Zachary Charles; Zheng Xu 002; Gauri Joshi; H. Brendan McMahan; Blaise Agüera y Arcas; Maruan Al-Shedivat; Galen Andrew; Salman Avestimehr; Katharine Daly; Deepesh Data; Suhas N. Diggavi; et al. (CoRR, 2021)

Secure Byzantine-Robust Distributed Learning via Clustering. - Raj Kiriti Velicheti; Derek Xia; Oluwasanmi Koyejo (CoRR, 2021)

Joint Gaussian Graphical Model Estimation: A Survey. - Katherine Tsai; Oluwasanmi Koyejo; Mladen Kolar (CoRR, 2021)

Does MAML Only Work via Feature Re-use? A Data Centric Perspective. - Brando Miranda; Yu-Xiong Wang; Sanmi Koyejo (CoRR, 2021)

Advances and Open Problems in Federated Learning. - Peter Kairouz; H. Brendan McMahan; Brendan Avent; Aurélien Bellet; Mehdi Bennis; Arjun Nitin Bhagoji; Kallista A. Bonawitz; Zachary Charles; Graham Cormode; Rachel Cummings; Rafael G. L. D'Oliveira; Hubert Eichner; et al. (Found. Trends Mach. Learn., 2021)

Controllable Radiance Fields for Dynamic Face Synthesis. - Peiye Zhuang; Liqian Ma; Sanmi Koyejo; Alexander G. Schwing (3DV, 2022)

Fully Automated Conversion Of Glioma Clinical MRI Scans Into A 3D Virtual Reality Model For Presurgical Planning. - Nick Tucker; Bradley P. Sutton; Chase Duncan; Colin Lu; Sanmi Koyejo; Andrew J. Tsung; Jane Maksimovic; Tate Ralph; Sister M. Pieta; Matthew T. Bramlet (ANNSIM, 2022)

Identifying Coarse-grained Independent Causal Mechanisms with Self-supervision. - Xiaoyang Wang; Klara Nahrstedt; Oluwasanmi Koyejo (CLeaR, 2022)

Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization. - Xiaojun Xu; Jacky Y. Zhang; Evelyn Ma; Hyun Ho Son; Sanmi Koyejo; Bo Li 026 (ICML, 2022)

EMIXER: End-to-end Multimodal X-ray Generation via Self-supervision. - Siddharth Biswal; Peiye Zhuang; Ayis Pyrros; Nasir Siddiqui; Sanmi Koyejo; Jimeng Sun 001 (MLHC, 2022)

A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction. - Yong Xie 002; Dakuo Wang; Pin-Yu Chen; Jinjun Xiong; Sijia Liu 001; Oluwasanmi Koyejo (NAACL-HLT, 2022)

A Reduction to Binary Approach for Debiasing Multiclass Datasets. - Ibrahim M. Alabdulmohsin; Jessica Schrouff; Sanmi Koyejo (NeurIPS, 2022)

CoPur: Certifiably Robust Collaborative Inference via Feature Purification. - Jing Liu; Chulin Xie; Sanmi Koyejo; Bo Li 026 (NeurIPS, 2022)

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. - Jessica Schrouff; Natalie Harris; Sanmi Koyejo; Ibrahim M. Alabdulmohsin; Eva Schnider; Krista Opsahl-Ong; Alexander Brown; Subhrajit Roy; Diana Mincu; Christina Chen; Awa Dieng; Yuan Liu; et al. (NeurIPS, 2022)

Fair Wrapping for Black-box Predictions. - Alexander Soen; Ibrahim M. Alabdulmohsin; Sanmi Koyejo; Yishay Mansour; Nyalleng Moorosi; Richard Nock; Ke Sun 001; Lexing Xie (NeurIPS, 2022)

Quadratic metric elicitation for fairness and beyond. - Gaurush Hiranandani; Jatin Mathur; Harikrishna Narasimhan; Oluwasanmi Koyejo (UAI, 2022)

ZenoPS: A Distributed Learning System Integrating Communication Efficiency and Security. - Cong Xie; Oluwasanmi Koyejo; Indranil Gupta (Algorithms, 2022)

Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? - Jessica Schrouff; Natalie Harris; Oluwasanmi Koyejo; Ibrahim Alabdulmohsin; Eva Schnider; Krista Opsahl-Ong; Alexander Brown; Subhrajit Roy; Diana Mincu; Christina Chen; Awa Dieng; Yuan Liu; et al. (CoRR, 2022)

Adversarially Robust Models may not Transfer Better: Sufficient Conditions for Domain Transferability from the View of Regularization. - Xiaojun Xu; Jacky Yibo Zhang; Evelyn Ma; Danny Son; Oluwasanmi Koyejo; Bo Li 026 (CoRR, 2022)

One Policy is Enough: Parallel Exploration with a Single Policy is Minimax Optimal for Reward-Free Reinforcement Learning. - Pedro Cisneros-Velarde; Boxiang Lyu; Sanmi Koyejo; Mladen Kolar (CoRR, 2022)

The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence. - Brando Miranda; Patrick Yu; Yu-Xiong Wang; Sanmi Koyejo (CoRR, 2022)

Invariant Aggregator for Defending Federated Backdoor Attacks. - Xiaoyang Wang; Dimitrios Dimitriadis; Sanmi Koyejo; Shruti Tople (CoRR, 2022)

Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing. - Klara Nahrstedt; Naresh R. Shanbhag; Vikram S. Adve; Nancy M. Amato; Romit Roy Choudhury; Carl A. Gunter; Nam Sung Kim; Olgica Milenkovic; Sayan Mitra; Lav R. Varshney; Yurii Vlasov; Sarita V. Adve; et al. (CoRR, 2022)

Latent Multimodal Functional Graphical Model Estimation. - Katherine Tsai; Boxin Zhao; Oluwasanmi Koyejo; Mladen Kolar (CoRR, 2022)

Batch Active Learning from the Perspective of Sparse Approximation. - Maohao Shen; Bowen Jiang 001; Jacky Yibo Zhang; Oluwasanmi Koyejo (CoRR, 2022)

Metric Elicitation; Moving from Theory to Practice. - Safinah Ali; Sohini Upadhyay; Gaurush Hiranandani; Elena L. Glassman; Oluwasanmi Koyejo (CoRR, 2022)

Target Conditioned Representation Independence (TCRI); From Domain-Invariant to Domain-General Representations. - Olawale Salaudeen; Oluwasanmi Koyejo (CoRR, 2022)

A Nonconvex Framework for Structured Dynamic Covariance Recovery. - Katherine Tsai; Mladen Kolar; Oluwasanmi Koyejo (J. Mach. Learn. Res., 2022)

Toward a Controllable Disentanglement Network. - Zengjie Song; Oluwasanmi Koyejo; Jiangshe Zhang 001 (IEEE Trans. Cybern., 2022)

Adapting to Latent Subgroup Shifts via Concepts and Proxies. - Ibrahim Alabdulmohsin; Nicole Chiou; Alexander D'Amour; Arthur Gretton; Sanmi Koyejo; Matt J. Kusner; Stephen R. Pfohl; Olawale Salaudeen; Jessica Schrouff; Katherine Tsai (AISTATS, 2023)

One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning. - Pedro Cisneros-Velarde; Boxiang Lyu; Sanmi Koyejo; Mladen Kolar (AISTATS, 2023)

Cooperative Inverse Decision Theory for Uncertain Preferences. - Zachary Robertson; Hantao Zhang; Sanmi Koyejo (AISTATS, 2023)

Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks. - Chulin Xie; Yunhui Long; Pin-Yu Chen; Qinbin Li; Sanmi Koyejo; Bo Li 026 (CCS, 2023)

Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions. - Boxiang Lyu; Zhe Feng; Zachary Robertson; Sanmi Koyejo (ICML, 2023)

Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells. - Rylan Schaeffer; Mikail Khona; Tzuhsuan Ma; Cristóbal Eyzaguirre; Sanmi Koyejo; Ila Fiete (NeurIPS, 2023)

Are Emergent Abilities of Large Language Models a Mirage? - Rylan Schaeffer; Brando Miranda; Sanmi Koyejo (NeurIPS, 2023)

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models. - Boxin Wang; Weixin Chen; Hengzhi Pei; Chulin Xie; Mintong Kang; Chenhui Zhang; Chejian Xu; Zidi Xiong; Ritik Dutta; Rylan Schaeffer; Sang T. Truong; Simran Arora; et al. (NeurIPS, 2023)

Finite-sample guarantees for Nash Q-learning with linear function approximation. - Pedro Cisneros-Velarde; Sanmi Koyejo (UAI, 2023)

Federated Domain Adaptation via Gradient Projection. - Enyi Jiang; Yibo Jacky Zhang; Oluwasanmi Koyejo (CoRR, 2023)

Double Descent Demystified: Identifying, Interpreting & Ablating the Sources of a Deep Learning Puzzle. - Rylan Schaeffer; Mikail Khona; Zachary Robertson; Akhilan Boopathy; Kateryna Pistunova; Jason W. Rocks; Ila Rani Fiete; Oluwasanmi Koyejo (CoRR, 2023)

Globalizing Fairness Attributes in Machine Learning: A Case Study on Health in Africa. - Mercy Nyamewaa Asiedu; Awa Dieng; Abigail Oppong; Maria Nagawa; Sanmi Koyejo; Katherine A. Heller (CoRR, 2023)

No Bidding, No Regret: Pairwise-Feedback Mechanisms for Digital Goods and Data Auctions. - Zachary Robertson; Oluwasanmi Koyejo (CoRR, 2023)

Layer-Wise Feedback Alignment is Conserved in Deep Neural Networks. - Zachary Robertson; Oluwasanmi Koyejo (CoRR, 2023)

Communication-Efficient Federated Learning through Importance Sampling. - Berivan Isik; Francesco Pase; Deniz Gündüz; Sanmi Koyejo; Tsachy Weissman; Michele Zorzi (CoRR, 2023)

Beyond Scale: the Diversity Coefficient as a Data Quality Metric Demonstrates LLMs are Pre-trained on Formally Diverse Data. - Alycia Lee; Brando Miranda; Sanmi Koyejo (CoRR, 2023)

Is Pre-training Truly Better Than Meta-Learning? - Brando Miranda; Patrick Yu; Saumya Goyal; Yu-Xiong Wang; Sanmi Koyejo (CoRR, 2023)

FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluation. - Dhruv Pai; Andres Carranza; Rylan Schaeffer; Arnuv Tandon; Sanmi Koyejo (CoRR, 2023)

Deceptive Alignment Monitoring. - Andres Carranza; Dhruv Pai; Rylan Schaeffer; Arnuv Tandon; Sanmi Koyejo (CoRR, 2023)

Invalid Logic, Equivalent Gains: The Bizarreness of Reasoning in Language Model Prompting. - Rylan Schaeffer; Kateryna Pistunova; Samar Khanna; Sarthak Consul; Sanmi Koyejo (CoRR, 2023)

Goodness-of-Fit of Attributed Probabilistic Graph Generative Models. - Pablo Robles-Granda; Katherine Tsai; Oluwasanmi Koyejo (CoRR, 2023)

Representation Engineering: A Top-Down Approach to AI Transparency. - Andy Zou; Long Phan; Sarah Li Chen; James Campbell; Phillip Guo; Richard Ren; Alexander Pan; Xuwang Yin; Mantas Mazeika; Ann-Kathrin Dombrowski; Shashwat Goel; Nathaniel Li; et al. (CoRR, 2023)

Learning to (Learn at Test Time). - Yu Sun 020; Xinhao Li; Karan Dalal; Chloe Hsu; Sanmi Koyejo; Carlos Guestrin; Xiaolong Wang 004; Tatsunori Hashimoto; Xinlei Chen (CoRR, 2023)

Incidental Polysemanticity. - Victor Lecomte; Kushal Thaman; Trevor Chow; Rylan Schaeffer; Sanmi Koyejo (CoRR, 2023)

Towards Fault-Tolerant Federated and Distributed Machine Learning. - Sanmi Koyejo (AAAI Spring Symposia, 2024)

Bayesian Optimization for Crop Genetics with Scalable Probabilistic Models. - Ruhana Azam; Sang T. Truong; Samuel B. Fernandes; Andrew D. B. Leakey; Alexander E. Lipka; Mohammed El-Kebir; Sanmi Koyejo (AABI, 2024)

Adaptive Compression in Federated Learning via Side Information. - Berivan Isik; Francesco Pase; Deniz Gündüz; Sanmi Koyejo; Tsachy Weissman; Michele Zorzi (AISTATS, 2024)

Causally Inspired Regularization Enables Domain General Representations. - Olawale Salaudeen; Sanmi Koyejo (AISTATS, 2024)

Proxy Methods for Domain Adaptation. - Katherine Tsai; Stephen R. Pfohl; Olawale Salaudeen; Nicole Chiou; Matt J. Kusner; Alexander D'Amour; Sanmi Koyejo; Arthur Gretton (AISTATS, 2024)

Invariant Aggregator for Defending against Federated Backdoor Attacks. - Xiaoyang Wang; Dimitrios Dimitriadis; Sanmi Koyejo; Shruti Tople (AISTATS, 2024)

The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africa. - Mercy Nyamewaa Asiedu; Awa Dieng; Iskandar Haykel; Negar Rostamzadeh; Stephen Pfohl; Chirag Nagpal; Maria Nagawa; Abigail Oppong; Sanmi Koyejo; Katherine A. Heller (EAAMO, 2024)

Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting. - Enyi Jiang; Yibo Jacky Zhang; Sanmi Koyejo (ICLR, 2024)

HIFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidance. - Junzhe Zhu; Peiye Zhuang; Sanmi Koyejo (ICLR, 2024)

Implicit Regularization in Feedback Alignment Learning Mechanisms for Neural Networks. - Zachary Robertson; Sanmi Koyejo (ICML, 2024)

Transforming and Combining Rewards for Aligning Large Language Models. - Zihao Wang; Chirag Nagpal; Jonathan Berant; Jacob Eisenstein; Alexander Nicholas D'Amour; Sanmi Koyejo; Victor Veitch (ICML, 2024)

Crossing Linguistic Horizons: Finetuning and Comprehensive Evaluation of Vietnamese Large Language Models. - Sang T. Truong; Duc Nguyen; Toan Nguyen; Dong D. Le; Nhi N. Truong; Tho Quan 001; Sanmi Koyejo (NAACL-HLT (Findings), 2024)

Sketching for Distributed Deep Learning: A Sharper Analysis. - Mayank Shrivastava; Berivan Isik; Qiaobo Li; Sanmi Koyejo; Arindam Banerjee 001 (NeurIPS, 2024)

Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections. - Nathan Stromberg; Rohan Ayyagari; Sanmi Koyejo; Richard Nock; Lalitha Sankar (NeurIPS, 2024)

Towards Trustworthy Large Language Models. - Sanmi Koyejo; Bo Li 026 (WSDM, 2024)

Investigating Data Contamination for Pre-training Language Models. - Minhao Jiang; Ken Ziyu Liu; Ming Zhong 005; Rylan Schaeffer; Siru Ouyang; Jiawei Han 001; Sanmi Koyejo (CoRR, 2024)

Scaling Laws for Downstream Task Performance of Large Language Models. - Berivan Isik; Natalia Ponomareva 001; Hussein Hazimeh 001; Dimitris Paparas; Sergei Vassilvitskii; Sanmi Koyejo (CoRR, 2024)

Rethinking Machine Unlearning for Large Language Models. - Sijia Liu 001; Yuanshun Yao; Jinghan Jia; Stephen Casper; Nathalie Baracaldo; Peter Hase; Xiaojun Xu; Yuguang Yao; Hang Li 001; Kush R. Varshney; Mohit Bansal; Sanmi Koyejo; et al. (CoRR, 2024)

Bridging Associative Memory and Probabilistic Modeling. - Rylan Schaeffer; Nika Zahedi; Mikail Khona; Dhruv Pai; Sang T. Truong; Yilun Du; Mitchell Ostrow; Sarthak Chandra; Andres Carranza; Ila Rani Fiete; Andrey Gromov; Sanmi Koyejo (CoRR, 2024)

Robustness to Subpopulation Shift with Domain Label Noise via Regularized Annotation of Domains. - Nathan Stromberg; Rohan Ayyagari; Monica Welfert; Sanmi Koyejo; Lalitha Sankar (CoRR, 2024)

Crossing Linguistic Horizons: Finetuning and Comprehensive Evaluation of Vietnamese Large Language Models. - Sang T. Truong; Duc Q. Nguyen; Toan Nguyen; Dong D. Le; Nhi N. Truong; Tho Quan 001; Sanmi Koyejo (CoRR, 2024)

Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data. - Matthias Gerstgrasser; Rylan Schaeffer; Apratim Dey; Rafael Rafailov; Henry Sleight; John Hughes; Tomasz Korbak; Rajashree Agrawal; Dhruv Pai; Andrey Gromov; Daniel A. Roberts; Diyi Yang; et al. (CoRR, 2024)

On Fairness of Low-Rank Adaptation of Large Models. - Zhoujie Ding; Ken Ziyu Liu; Pura Peetathawatchai; Berivan Isik; Sanmi Koyejo (CoRR, 2024)

Scalable Ensembling For Mitigating Reward Overoptimisation. - Ahmed M. Ahmed; Rafael Rafailov; Stepan Sharkov; Xuechen Li; Sanmi Koyejo (CoRR, 2024)

Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive? - Rylan Schaeffer; Hailey Schoelkopf; Brando Miranda; Gabriel Mukobi; Varun Madan; Adam Ibrahim; Herbie Bradley; Stella Biderman; Sanmi Koyejo (CoRR, 2024)

Towards an Improved Understanding and Utilization of Maximum Manifold Capacity Representations. - Rylan Schaeffer; Victor Lecomte; Dhruv Bhandarkar Pai; Andres Carranza; Berivan Isik; Alyssa Unell; Mikail Khona; Thomas E. Yerxa; Yann LeCun; SueYeon Chung; Andrey Gromov; Ravid Shwartz-Ziv; et al. (CoRR, 2024)

Label Noise Robustness for Domain-Agnostic Fair Corrections via Nearest Neighbors Label Spreading. - Nathan Stromberg; Rohan Ayyagari; Sanmi Koyejo; Richard Nock; Lalitha Sankar (CoRR, 2024)

Quantifying Variance in Evaluation Benchmarks. - Lovish Madaan; Aaditya K. Singh; Rylan Schaeffer; Andrew Poulton; Sanmi Koyejo; Pontus Stenetorp; Sharan Narang; Dieuwke Hupkes (CoRR, 2024)

In-Context Learning of Energy Functions. - Rylan Schaeffer; Mikail Khona; Sanmi Koyejo (CoRR, 2024)

Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs. - Ashwinee Panda; Berivan Isik; Xiangyu Qi; Sanmi Koyejo; Tsachy Weissman; Prateek Mittal (CoRR, 2024)

Learning to (Learn at Test Time): RNNs with Expressive Hidden States. - Yu Sun 020; Xinhao Li; Karan Dalal; Jiarui Xu; Arjun Vikram; Genghan Zhang; Yann Dubois; Xinlei Chen; Xiaolong Wang 004; Sanmi Koyejo; Tatsunori Hashimoto; Carlos Guestrin (CoRR, 2024)

Open Problems in Technical AI Governance. - Anka Reuel; Ben Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (CoRR, 2024)

When Do Universal Image Jailbreaks Transfer Between Vision-Language Models? - Rylan Schaeffer; Dan Valentine; Luke Bailey; James Chua; Cristóbal Eyzaguirre; Zane Durante; Joe Benton; Brando Miranda; Henry Sleight; John Hughes; Rajashree Agrawal; Mrinank Sharma; et al. (CoRR, 2024)

Building a Domain-specific Guardrail Model in Production. - Mohammad Niknazar; Paul V. Haley; Latha Ramanan; Sang T. Truong; Yedendra Shrinivasan; Ayan Kumar Bhowmick; Prasenjit Dey; Ashish Jagmohan; Hema Maheshwari; Shom Ponoth; Robert Smith; Aditya Vempaty; et al. (CoRR, 2024)

Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World. - Joshua Kazdan; Rylan Schaeffer; Apratim Dey; Matthias Gerstgrasser; Rafael Rafailov; David L. Donoho; Sanmi Koyejo (CoRR, 2024)

ZIP-FIT: Embedding-Free Data Selection via Compression-Based Alignment. - Elyas Obbad; Iddah Mlauzi; Brando Miranda; Rylan Schaeffer; Kamal Obbad; Suhana Bedi; Sanmi Koyejo (CoRR, 2024)

Differentially Private Adaptation of Diffusion Models via Noisy Aggregated Embeddings. - Pura Peetathawatchai; Wei-Ning Chen; Berivan Isik; Sanmi Koyejo; Albert No (CoRR, 2024)

Shaping AI's Impact on Billions of Lives. - Mariano-Florentino Cuellar; Jeff Dean; Finale Doshi-Velez; John L. Hennessy; Andy Konwinski; Sanmi Koyejo; Pelonomi Moiloa; Emma Pierson; David A. Patterson 001 (CoRR, 2024)

Best-of-N Jailbreaking. - John Hughes; Sara Price; Aengus Lynch; Rylan Schaeffer; Fazl Barez; Sanmi Koyejo; Henry Sleight; Erik Jones; Ethan Perez; Mrinank Sharma (CoRR, 2024)

MoSH: Modeling Multi-Objective Tradeoffs with Soft and Hard Bounds. - Edward Chen; Natalie Dullerud; Thomas Niedermayr; Elizabeth Kidd; Ransalu Senanayake; Pang Wei Koh; Sanmi Koyejo; Carlos Guestrin (CoRR, 2024)

Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice. - A. Feder Cooper; Christopher A. Choquette-Choo; Miranda Bogen; Matthew Jagielski; Katja Filippova; Ken Ziyu Liu; Alexandra Chouldechova; Jamie Hayes; Yangsibo Huang; Niloofar Mireshghallah; Ilia Shumailov; Eleni Triantafillou; et al. (CoRR, 2024)

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs. - Michael Wornow; Suhana Bedi; Miguel Angel Fuentes Hernandez; Ethan Steinberg; Jason Alan Fries; Christopher Ré; Sanmi Koyejo; Nigam H. Shah (CoRR, 2024)

For Robust Worst-Group Accuracy, Ignore Group Annotations. - Nathan Stromberg; Rohan Ayyagari; Monica Welfert; Sanmi Koyejo; Richard Nock; Lalitha Sankar (Trans. Mach. Learn. Res., 2024)

Personalized Federated Learning with Spurious Features: An Adversarial Approach. - Xiaoyang Wang; Han Zhao 002; Klara Nahrstedt; Sanmi Koyejo (Trans. Mach. Learn. Res., 2024)

Artificial Intelligence, Social Responsibility, and the Roles of the University. - Michael C. Loui; Nigel Bosch; Anita Say Chan; Jenny L. Davis; Rochelle Gutiérrez; Jingrui He; Karrie Karahalios; Sanmi Koyejo; Ruby Mendenhall; Madelyn Rose Sanfilippo; Hanghang Tong; Lav R. Varshney; et al. (Commun. ACM, 2024)

Increasing the presence of BIPOC researchers in computational science. - Christine Yifeng Chen; Alan Christoffels; Roger Dube; Kamuela Enos; Juan E. Gilbert; Sanmi Koyejo; Jason Leigh; Carlo Liquido; Amy McKee; Kari Noe; Tai-Quan Peng; Karaitiana Taiuru (Nat. Comput. Sci., 2024)

Publisher Correction: Increasing the presence of BIPOC researchers in computational science. - Christine Yifeng Chen; Alan Christoffels; Roger Dube; Kamuela Enos; Juan E. Gilbert; Sanmi Koyejo; Jason Leigh; Carlo Liquido; Amy McKee; Kari Noe; Tai-Quan Peng; Karaitiana Taiuru (Nat. Comput. Sci., 2024)

Fairness through Difference Awareness: Measuring Desired Group Discrimination in LLMs. - Angelina Wang; Michelle Phan; Daniel E. Ho; Sanmi Koyejo (ACL (1), 2025)

Decision from Suboptimal Classifiers: Excess Risk Pre- and Post-Calibration. - Alexandre Perez-Lebel; Gaël Varoquaux; Sanmi Koyejo; Matthieu Doutreligne; Marine Le Morvan (AISTATS, 2025)

Improving Generative AI Student Feedback: Direct Preference Optimization with Teachers in the Loop. - Juliette Woodrow; Chris Piech; Sanmi Koyejo (EDM, 2025)

The Reality of AI and Biorisk. - Aidan Peppin; Anka Reuel; Stephen Casper; Elliot Jones; Andrew Strait; Usman Anwar; Anurag Agrawal; Sayash Kapoor; Sanmi Koyejo; Marie Pellat; Rishi Bommasani; Nick Frosst; et al. (FAccT, 2025)

The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning. - Youssef Allouah; Joshua Kazdan; Rachid Guerraoui; Sanmi Koyejo (ICLR, 2025)

Scaling Laws for Downstream Task Performance in Machine Translation. - Berivan Isik; Natalia Ponomareva 001; Hussein Hazimeh 001; Dimitris Paparas; Sergei Vassilvitskii; Sanmi Koyejo (ICLR, 2025)

Failures to Find Transferable Image Jailbreaks Between Vision-Language Models. - Rylan Schaeffer; Dan Valentine; Luke Bailey; James Chua; Cristóbal Eyzaguirre; Zane Durante; Joe Benton; Brando Miranda; Henry Sleight; Tony Tong Wang; John Hughes; Rajashree Agrawal; et al. (ICLR, 2025)

Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data. - Michael Wornow; Suhana Bedi; Miguel Angel Fuentes Hernandez; Ethan Steinberg; Jason Alan Fries; Christopher Ré; Sanmi Koyejo; Nigam Shah (ICLR, 2025)

More than Marketing? On the Information Value of AI Benchmarks for Practitioners. - Amelia F. Hardy; Anka Reuel; Kiana Jafari Meimandi; Lisa Soder; Allie Griffith; Dylan M. Asmar; Sanmi Koyejo; Michael S. Bernstein; Mykel John Kochenderfer (IUI, 2025)

Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4. - Leni Aniva; Chuyue Sun; Brando Miranda; Clark W. Barrett; Sanmi Koyejo (TACAS (1), 2025)

Trustworthy Machine Learning: From Data to Models. - Bo Han 003; Jiangchao Yao; Tongliang Liu; Bo Li; Sanmi Koyejo; Feng Liu (Found. Trends Priv. Secur., 2025)

Rethinking machine unlearning for large language models. - Sijia Liu 001; Yuanshun Yao; Jinghan Jia; Stephen Casper; Nathalie Baracaldo; Peter Hase; Yuguang Yao; Chris Yuhao Liu; Xiaojun Xu; Hang Li 001; Kush R. Varshney; Mohit Bansal; et al. (Nat. Mac. Intell., 2025)

Optimization and Generalization Guarantees for Weight Normalization. - Pedro Cisneros-Velarde; Zhijie Chen; Sanmi Koyejo; Arindam Banerjee 001 (Trans. Mach. Learn. Res., 2025)

Open Problems in Technical AI Governance. - Anka Reuel; Benjamin Bucknall; Stephen Casper; Timothy Fist; Lisa Soder; Onni Aarne; Lewis Hammond; Lujain Ibrahim; Alan Chan; Peter Wills; Markus Anderljung; Ben Garfinkel; et al. (Trans. Mach. Learn. Res., 2025)

Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified? - Olawale Salaudeen; Nicole Chiou; Shiny Weng; Sanmi Koyejo (Trans. Mach. Learn. Res., 2025)

High-Dimensional Markov-switching Ordinary Differential Processes. - Katherine Tsai; Mladen Kolar; Sanmi Koyejo (CoRR, 2025)

Logits are All We Need to Adapt Closed Models. - Gaurush Hiranandani; Haolun Wu; Subhojyoti Mukherjee; Sanmi Koyejo (CoRR, 2025)

SycEval: Evaluating LLM Sycophancy. - Aaron Fanous; Jacob Goldberg; Ank A. Agarwal; Joanna Lin; Anson Zhou; Roxana Daneshjou; Sanmi Koyejo (CoRR, 2025)

KGGen: Extracting Knowledge Graphs from Plain Text with Language Models. - Belinda Mo; Kyssen Yu; Joshua Kazdan; Proud Mpala; Lisa Yu; Chris Cundy; Charilaos I. Kanatsoulis; Sanmi Koyejo (CoRR, 2025)

Lean-ing on Quality: How High-Quality Data Beats Diverse Multilingual Data in AutoFormalization. - Willy Chan; Michael Souliman; Jakob Nordhagen; Brando Miranda; Elyas Obbad; Oluwasanmi Koyejo (CoRR, 2025)

How Do Large Language Monkeys Get Their Power (Laws)? - Rylan Schaeffer; Joshua Kazdan; John Hughes; Jordan Juravsky; Sara Price; Aengus Lynch; Erik Jones; Robert Kirk; Azalia Mirhoseini; Sanmi Koyejo (CoRR, 2025)

Aligning Compound AI Systems via System-level DPO. - Xiangwen Wang; Yibo Jacky Zhang; Zhoujie Ding; Katherine Tsai; Sanmi Koyejo (CoRR, 2025)

Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks. - Rylan Schaeffer; Punit Singh Koura; Binh Tang; Ranjan Subramanian; Aaditya K. Singh; Todor Mihaylov; Prajjwal Bhargava; Lovish Madaan; Niladri S. Chatterji; Vedanuj Goswami; Sergey Edunov; Dieuwke Hupkes; et al. (CoRR, 2025)

No, of course I can! Refusal Mechanisms Can Be Exploited Using Harmless Fine-Tuning Data. - Joshua Kazdan; Lisa Yu; Rylan Schaeffer; Chris Cundy; Sanmi Koyejo; Dvijotham Krishnamurthy (CoRR, 2025)

Position: Model Collapse Does Not Mean What You Think. - Rylan Schaeffer; Joshua Kazdan; Alvan Caleb Arulandu; Sanmi Koyejo (CoRR, 2025)

TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records. - Hejie Cui; Alyssa Unell; Bowen Chen; Jason Alan Fries; Emily Alsentzer; Sanmi Koyejo; Nigam Shah (CoRR, 2025)

Toward an Evaluation Science for Generative AI Systems. - Laura Weidinger; Inioluwa Deborah Raji; Hanna M. Wallach; Margaret Mitchell; Angelina Wang; Olawale Salaudeen; Rishi Bommasani; Deep Ganguli; Sanmi Koyejo; William Isaac 001 (CoRR, 2025)

Reliable and Efficient Amortized Model-based Evaluation. - Sang T. Truong; Yuheng Tu; Percy Liang; Bo Li 026; Sanmi Koyejo (CoRR, 2025)

AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration. - Andy Zhou; Kevin Wu; Francesco Pinto; Zhaorun Chen; Yi Zeng 005; Yu Yang 011; Shuang Yang; Sanmi Koyejo; James Zou; Bo Li 026 (CoRR, 2025)

Preferential Multi-Objective Bayesian Optimization for Drug Discovery. - Tai Dang; Long-Hung Pham; Sang T. Truong; Ari Glenn; Wendy Nguyen; Edward A. Pham; Jeffrey S. Glenn; Sanmi Koyejo; Thang Luong (CoRR, 2025)

Language Models May Verbatim Complete Text They Were Not Explicitly Trained On. - Ken Ziyu Liu; Christopher A. Choquette-Choo; Matthew Jagielski; Peter Kairouz; Sanmi Koyejo; Percy Liang; Nicolas Papernot (CoRR, 2025)

Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF. - Syrine Belakaria; Joshua Kazdan; Charles Marx; Chris Cundy; Willie Neiswanger; Sanmi Koyejo; Barbara E. Engelhardt; Stefano Ermon (CoRR, 2025)

Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models. - Zhanke Zhou; Zhaocheng Zhu; Xuan Li 005; Mikhail Galkin 001; Xiao Feng 003; Sanmi Koyejo; Jian Tang 005; Bo Han 003 (CoRR, 2025)

One-Minute Video Generation with Test-Time Training. - Karan Dalal; Daniel Koceja; Gashon Hussein; Jiarui Xu; Yue Zhao 006; Youjin Song; Shihao Han; Ka Chun Cheung; Jan Kautz; Carlos Guestrin; Tatsunori Hashimoto; Sanmi Koyejo; et al. (CoRR, 2025)

A Framework for Objective-Driven Dynamical Stochastic Fields. - Yibo Jacky Zhang; Sanmi Koyejo (CoRR, 2025)

The Leaderboard Illusion. - Shivalika Singh; Yiyang Nan; Alex Wang; Daniel D'souza; Sayash Kapoor; Ahmet Üstün; Sanmi Koyejo; Yuntian Deng; Shayne Longpre; Noah Smith; Beyza Ermis; Marzieh Fadaee; et al. (CoRR, 2025)

Measurement to Meaning: A Validity-Centered Framework for AI Evaluation. - Olawale Salaudeen; Anka Reuel; Ahmed Ahmed; Suhana Bedi; Zachary Robertson; Sudharsan Sundar; Ben Domingue; Angelina Wang; Sanmi Koyejo (CoRR, 2025)

SATBench: Benchmarking LLMs' Logical Reasoning via Automated Puzzle Generation from SAT Formulas. - Anjiang Wei; Yuheng Wu; Yingjia Wan; Tarun Suresh; Huanmi Tan; Zhanke Zhou; Sanmi Koyejo; Ke Wang; Alex Aiken (CoRR, 2025)

MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks. - Suhana Bedi; Hejie Cui; Miguel Fuentes; Alyssa Unell; Michael Wornow; Juan M. Banda; Nikesh Kotecha; Timothy Keyes; Yifan Mai 001; Mert Oez; Hao Qiu; Shrey Jain; et al. (CoRR, 2025)

Understanding challenges to the interpretation of disaggregated evaluations of algorithmic fairness. - Stephen R. Pfohl; Natalie Harris; Chirag Nagpal; David Madras; Vishwali Mhasawade; Olawale Salaudeen; Awa Dieng; Shannon Sequeira; Santiago Eduardo Arciniegas; Lillian Sung; Nnamdi Ezeanochie; Heather Cole-Lewis; et al. (CoRR, 2025)

The Optimization Paradox in Clinical AI Multi-Agent Systems. - Suhana Bedi; Iddah Mlauzi; Daniel Shin; Sanmi Koyejo; Nigam H. Shah (CoRR, 2025)

Certified Unlearning for Neural Networks. - Anastasia Koloskova; Youssef Allouah; Animesh Jha; Rachid Guerraoui; Sanmi Koyejo (CoRR, 2025)

From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? - Zhanke Zhou; Xiao Feng 003; Zhaocheng Zhu; Jiangchao Yao; Sanmi Koyejo; Bo Han 003 (CoRR, 2025)

Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track. - Rylan Schaeffer; Joshua Kazdan; Yegor Denisov-Blanch; Brando Miranda; Matthias Gerstgrasser; Susan Zhang; Andreas Haupt; Isha Gupta; Elyas Obbad; Jesse Dodge; Jessica Zosa Forde; Koustuv Sinha; et al. (CoRR, 2025)

Interactive Multi-Objective Probabilistic Preference Learning with Soft and Hard Bounds. - Edward Chen; Sang T. Truong; Natalie Dullerud; Sanmi Koyejo; Carlos Guestrin (CoRR, 2025)

Expert-level validation of AI-generated medical text with scalable language models. - Asad Aali; Vasiliki Bikia; Maya Varma; Nicole Chiou; Sophie Ostmeier; Arnav Singhvi; Magdalini Paschali; Ashwin Kumar; Andrew Johnston; Karimar Amador-Martinez; Eduardo Juan Perez Guerrero; Paola Naovi Cruz Rivera; et al. (CoRR, 2025)

Distributional Unlearning: Forgetting Distributions, Not Just Samples. - Youssef Allouah; Rachid Guerraoui; Sanmi Koyejo (CoRR, 2025)

Advancing Science- and Evidence-based AI Policy. - Rishi Bommasani; Sanjeev Arora; Jennifer T. Chayes; Yejin Choi 001; Mariano-Florentino Cuellar; Li Fei-Fei 001; Daniel E. Ho; Dan Jurafsky; Sanmi Koyejo; Hima Lakkaraju; Arvind Narayanan; Alondra Nelson; et al. (CoRR, 2025)

Let's Measure Information Step-by-Step: LLM-Based Evaluation Beyond Vibes. - Zachary Robertson; Sanmi Koyejo (CoRR, 2025)

Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs. - Aryan Gulati; Brando Miranda; Eric Chen; Emily Xia; Kai Fronsdal; Bruno Dumont; Elyas Obbad; Sanmi Koyejo (CoRR, 2025)

Algorithmic Fairness amid Social Determinants: Reflection, Characterization, and Approach. - Zeyu Tang 002; Alex John London; Atoosa Kasirzadeh; Sanmi Koyejo; Peter Spirtes; Kun Zhang 001 (CoRR, 2025)