Boundless: Generative Adversarial Networks for Image Extension. - Dilip Krishnan; Piotr Teterwak; Aaron Sarna; Aaron Maschinot; Ce Liu 001; David Belanger 002; William T. Freeman (ICCV, 2019)

Supervised Contrastive Learning. - Prannay Khosla; Piotr Teterwak; Chen Wang 050; Aaron Sarna; Yonglong Tian; Phillip Isola; Aaron Maschinot; Ce Liu 001; Dilip Krishnan (NeurIPS, 2020)

OCONet: Image Extrapolation by Object Completion. - Richard Strong Bowen; Huiwen Chang; Charles Herrmann; Piotr Teterwak; Ce Liu 001; Ramin Zabih (CVPR, 2021)

Tune it the Right Way: Unsupervised Validation of Domain Adaptation via Soft Neighborhood Density. - Kuniaki Saito; Donghyun Kim 006; Piotr Teterwak; Stan Sclaroff; Trevor Darrell; Kate Saenko (ICCV, 2021)

Understanding Invariance via Feedforward Inversion of Discriminatively Trained Classifiers. - Piotr Teterwak; Chiyuan Zhang; Dilip Krishnan; Michael C. Mozer (ICML, 2021)

VisDA-2021 Competition: Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data. - Dina Bashkirova; Dan Hendrycks; Donghyun Kim 006; Haojin Liao; Samarth Mishra; Chandramouli Rajagopalan; Kate Saenko; Kuniaki Saito; Burhan Ul Tayyab; Piotr Teterwak; Ben Usman (NeurIPS (Competition and Demos), 2021)

VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting. - Dina Bashkirova; Samarth Mishra; Diala Lteif; Piotr Teterwak; Donghyun Kim 006; Fadi M. Alladkani; James Akl; Berk Çalli; Sarah Adel Bargal; Kate Saenko; Daehan Kim; Minseok Seo; et al. (NeurIPS (Competition and Demos), 2021)

VisDA-2021 Competition Universal Domain Adaptation to Improve Performance on Out-of-Distribution Data. - Dina Bashkirova; Dan Hendrycks; Donghyun Kim 006; Samarth Mishra; Kate Saenko; Kuniaki Saito; Piotr Teterwak; Ben Usman (CoRR, 2021)

Mind the Backbone: Minimizing Backbone Distortion for Robust Object Detection. - Kuniaki Saito; Donghyun Kim 006; Piotr Teterwak; Rogério Feris; Kate Saenko (CoRR, 2023)

CLAMP: Contrastive LAnguage Model Prompt-tuning. - Piotr Teterwak; Ximeng Sun; Bryan A. Plummer; Kate Saenko; Ser-Nam Lim (CoRR, 2023)

MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters. - Chau Pham 001; Piotr Teterwak; Soren Nelson; Bryan A. Plummer (WACV, 2024)

Learning to Compose SuperWeights for Neural Parameter Allocation Search. - Piotr Teterwak; Soren Nelson; Nikoli Dryden; Dina Bashkirova; Kate Saenko; Bryan A. Plummer (WACV, 2024)

Vision-LLMs Can Fool Themselves with Self-Generated Typographic Attacks. - Maan Qraitem; Nazia Tasnim; Piotr Teterwak; Kate Saenko; Bryan A. Plummer (CoRR, 2024)

SLANT: Spurious Logo ANalysis Toolkit. - Maan Qraitem; Piotr Teterwak; Kate Saenko; Bryan A. Plummer (CoRR, 2024)

OP-LoRA: The Blessing of Dimensionality. - Piotr Teterwak; Kate Saenko; Bryan A. Plummer; Ser-Nam Lim (CoRR, 2024)

Is Large-scale Pretraining the Secret to Good Domain Generalization? - Piotr Teterwak; Kuniaki Saito; Theodoros Tsiligkaridis; Bryan A. Plummer; Kate Saenko (ICLR, 2025)

ERM++: An Improved Baseline for Domain Generalization. - Piotr Teterwak; Kuniaki Saito; Theodoros Tsiligkaridis; Kate Saenko; Bryan A. Plummer (WACV, 2025)

Web Artifact Attacks Disrupt Vision Language Models. - Maan Qraitem; Piotr Teterwak; Kate Saenko; Bryan A. Plummer (CoRR, 2025)