Sayna Ebrahimi

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 44

Top Topics

Active Learning

Kolmogorov Smirnov

Structured And Unstructured Data

Top Venues

Publications

Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. Trans. Mach. Learn. Res. 2024 (2024)
Pritam Sarkar, Sayna Ebrahimi, Ali Etemad, Ahmad Beirami, Sercan Ö. Arik, Tomas Pfister
Mitigating Object Hallucination via Data Augmented Contrastive Tuning. CoRR (2024)
James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister
TextGenSHAP: Scalable Post-Hoc Explanations in Text Generation with Long Documents. ACL (Findings) (2024)
James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents. CoRR (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. CoRR (2023)
Qingyao Sun, Kevin P. Murphy, Sayna Ebrahimi, Alexander D'Amour
Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations. NeurIPS (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. CoRR (2023)
Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister
Test-Time Adaptation for Visual Document Understanding. Trans. Mach. Learn. Res. 2023 (2023)
Sayna Ebrahimi, Sercan Ö. Arik, Yihe Dong, Tomas Pfister
LANISTR: Multimodal Learning from Structured and Unstructured Data. CoRR (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö Arik, Tomas Pfister, Somesh Jha
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. EMNLP (Findings) (2023)
Nicasia Beebe-Wang, Sayna Ebrahimi, Jinsung Yoon, Sercan Ö. Arik, Tomas Pfister
PAITS: Pretraining and Augmentation for Irregularly-Sampled Time Series. CoRR (2023)
Qingyao Sun, Kevin Murphy, Sayna Ebrahimi, Alexander D'Amour
Beyond Invariance: Test-Time Label-Shift Adaptation for Distributions with "Spurious" Correlations. CoRR (2022)
Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister
DualPrompt: Complementary Prompting for Rehearsal-free Continual Learning. CoRR (2022)
Shizhan Zhu, Sayna Ebrahimi, Angjoo Kanazawa, Trevor Darrell
Differentiable Gradient Sampling for Learning Implicit 3D Scene Reconstructions from a Single Image. ICLR (2022)
Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer G. Dy, Tomas Pfister
DualPrompt: Complementary Prompting for Rehearsal-Free Continual Learning. ECCV (26) (2022)
Dian Chen, Dequan Wang, Trevor Darrell, Sayna Ebrahimi
Contrastive Test-Time Adaptation. CoRR (2022)
Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister
Test-Time Adaptation for Visual Document Understanding. CoRR (2022)
Colorado J. Reed, Xiangyu Yue, Ani Nrusimha, Sayna Ebrahimi, Vivek Vijaykumar, Richard Mao, Bo Li, Shanghang Zhang, Devin Guillory, Sean Metzger, Kurt Keutzer, Trevor Darrell
Self-Supervised Pretraining Improves Self-Supervised Pretraining. WACV (2022)
Dian Chen, Dequan Wang, Trevor Darrell, Sayna Ebrahimi
Contrastive Test-Time Adaptation. CVPR (2022)
Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt
Predicting with Confidence on Unseen Distributions. CoRR (2021)
Colorado J. Reed, Xiangyu Yue, Ani Nrusimha, Sayna Ebrahimi, Vivek Vijaykumar, Richard Mao, Bo Li, Shanghang Zhang, Devin Guillory, Sean Metzger, Kurt Keutzer, Trevor Darrell
Self-Supervised Pretraining Improves Self-Supervised Pretraining. CoRR (2021)
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E. Gonzalez, Marcus Rohrbach, Trevor Darrell
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting. ICLR (2021)
Devin Guillory, Vaishaal Shankar, Sayna Ebrahimi, Trevor Darrell, Ludwig Schmidt
Predicting with Confidence on Unseen Distributions. ICCV (2021)
Michael Laielli, Giscard Biamby, Dian Chen, Adam Loeffler, Phat Dat Nguyen, Ross Luo, Trevor Darrell, Sayna Ebrahimi
Region-level Active Learning for Cluttered Scenes. CoRR (2021)
Dequan Wang, Shaoteng Liu, Sayna Ebrahimi, Evan Shelhamer, Trevor Darrell
On-target Adaptation. CoRR (2021)
Sayna Ebrahimi, Franziska Meier, Roberto Calandra, Trevor Darrell, Marcus Rohrbach
Adversarial Continual Learning. CoRR (2020)
Sayna Ebrahimi, William Gan, Kamyar Salahi, Trevor Darrell
Minimax Active Learning. CoRR (2020)
Samaneh Azadi, Deepak Pathak, Sayna Ebrahimi, Trevor Darrell
Compositional GAN: Learning Image-Conditional Binary Composition. Int. J. Comput. Vis. 128 (10) (2020)
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E. Gonzalez, Marcus Rohrbach, Trevor Darrell
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting. CoRR (2020)
Sayna Ebrahimi, Franziska Meier, Roberto Calandra, Trevor Darrell, Marcus Rohrbach
Adversarial Continual Learning. ECCV (11) (2020)
Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach
Uncertainty-guided Continual Learning with Bayesian Neural Networks. ICLR (2020)
Samarth Sinha, Sayna Ebrahimi, Trevor Darrell
Variational Adversarial Active Learning. ICCV (2019)
Samarth Sinha, Sayna Ebrahimi, Trevor Darrell
Variational Adversarial Active Learning. CoRR (2019)
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. CVPR (2019)
Irene Amerini, Elena Balashova, Sayna Ebrahimi, Kathryn Leonard, Arsha Nagrani, Amaia Salvador
WiCV 2019: The Sixth Women In Computer Vision Workshop. CVPR Workshops (2019)
Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach
Uncertainty-guided Continual Learning with Bayesian Neural Networks. CoRR (2019)
Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach
Uncertainty-Guided Continual Learning in Bayesian Neural Networks - Extended Abstract. CVPR Workshops (2019)
Samaneh Azadi, Deepak Pathak, Sayna Ebrahimi, Trevor Darrell
Compositional GAN (Extended Abstract): Learning Image-Conditional Binary Composition. DGS@ICLR (2019)
Irene Amerini, Elena Balashova, Sayna Ebrahimi, Kathryn Leonard, Arsha Nagrani, Amaia Salvador
WiCV 2019: The Sixth Women In Computer Vision Workshop. CoRR (2019)
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata
Generalized Zero-Shot Learning via Aligned Variational Autoencoders. CVPR Workshops (2019)
Samaneh Azadi, Deepak Pathak, Sayna Ebrahimi, Trevor Darrell
Compositional GAN: Learning Conditional Image Composition. CoRR (2018)
Edgar Schönfeld, Sayna Ebrahimi, Samarth Sinha, Trevor Darrell, Zeynep Akata
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders. CoRR (2018)
Sayna Ebrahimi, Anna Rohrbach, Trevor Darrell
Gradient-free Policy Architecture Search and Adaptation. CoRR (2017)
Sayna Ebrahimi, Anna Rohrbach, Trevor Darrell
Gradient-free Policy Architecture Search and Adaptation. CoRL (2017)