Mikhail Yurochkin

LiveXiv - A Multi-Modal live benchmark based on Arxiv papers content ICLR 2025 A transfer learning framework for weak to strong generalization ICLR 2025 Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead ICML 2025 SPRI: Aligning Large Language Models with Context-Situated Principles ICML 2025 Speculate, then Collaborate: Fusing Knowledge of Language Models during Decoding ICML 2025 tinyBenchmarks: evaluating LLMs with fewer examples ICML 2024 Uncertainty Quantification via Stable Distribution Propagation ICLR 2024 Fusing Models with Complementary Expertise ICLR 2024 An Investigation of Representation and Allocation Harms in Contrastive Learning ICLR 2024 Efficient multi-prompt evaluation of LLMs NIPS 2024 Distributional Preference Alignment of LLMs via Optimal Transport NIPS 2024 Weak Supervision Performance Evaluation via Partial Identification NIPS 2024 Aligners: Decoupling LLMs and Alignment EMNLP 2024 Asymmetry in Low-Rank Adapters of Foundation Models ICML 2024 Risk Aware Benchmarking of Large Language Models ICML 2024 Simple Disentanglement of Style and Content in Visual Representations ICML 2023 Learning Proximal Operators to Discover Multiple Optima ICLR 2023 Understanding new tasks through the lens of training data via exponential tilting ICLR 2023 Sampling with Mollified Interaction Energy Descent ICLR 2023 Measuring the robustness of Gaussian processes to kernel choice AISTATS 2022 Calibrated Data-Dependent Constraints with Exact Satisfaction Guarantees NIPS 2022 Your fairness may vary: Pretrained language model fairness in toxic text classification ACL 2022 Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets ICML 2022 Domain Adaptation meets Individual Fairness. And they get along. NIPS 2022 On efficient multilevel Clustering via Wasserstein distances JMLR 2021 On sensitivity of meta-learning to support data NIPS 2021 Does enforcing fairness mitigate biases caused by subpopulation shift? NIPS 2021 Post-processing for Individual Fairness NIPS 2021 Individually Fair Rankings ICLR 2021 Statistical inference for individual fairness ICLR 2021 SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness ICLR 2021 Individually Fair Gradient Boosting ICLR 2021 Outlier-Robust Optimal Transport ICML 2021 Training individually fair ML models with sensitive subspace robustness ICLR 2020 Model Fusion with Kullback-Leibler Divergence ICML 2020 Two Simple Ways to Learn Individual Fairness Metrics from Data ICML 2020 Auditing ML Models for Individual Bias and Unfairness AISTATS 2020 Continuous Regularized Wasserstein Barycenters NIPS 2020 Federated Learning with Matched Averaging ICLR 2020 Bayesian Nonparametric Federated Learning of Neural Networks ICML 2019 Dirichlet Simplex Nest and Geometric Inference ICML 2019 Hierarchical Optimal Transport for Document Representation NIPS 2019 Statistical Model Aggregation via Parameter Matching NIPS 2019 Alleviating Label Switching with Optimal Transport NIPS 2019 Scalable inference of topic evolution via models for latent geometric structures NIPS 2019 Multilevel Clustering via Wasserstein Means ICML 2017 Multi-way Interacting Regression via Factorization Machines NIPS 2017 Conic Scan-and-Cover algorithms for nonparametric topic modeling NIPS 2017 Geometric Dirichlet Means Algorithm for topic inference NIPS 2016