A segment-based audio-visual speech recognizer: data collection, development, and initial experiments. - Timothy J. Hazen; Kate Saenko; Chia-Hao La; James R. Glass (ICMI, 2004)

Articulatory features for robust visual speech recognition. - Kate Saenko; Trevor Darrell; James R. Glass (ICMI, 2004)

Production domain modeling of pronunciation for visual speech recognition. - Kate Saenko; Karen Livescu; James R. Glass; Trevor Darrell (ICASSP (5), 2005)

Visual Speech Recognition with Loosely Synchronized Feature Streams. - Kate Saenko; Karen Livescu; Michael Siracusa; Kevin W. Wilson; James R. Glass; Trevor Darrell (ICCV, 2005)

Co-Adaptation of audio-visual speech and gesture classifiers. - C. Mario Christoudias; Kate Saenko; Louis-Philippe Morency; Trevor Darrell (ICMI, 2006)

An Asynchronous DBN for Audio-Visual speech Recognition. - Kate Saenko; Karen Livescu (SLT, 2006)

Articulatory Feature-Based Methods for Acoustic and Audio-Visual Speech Recognition: Summary from the 2006 JHU Summer workshop. - Karen Livescu; Özgür Çetin; Mark Hasegawa-Johnson; Simon King 001; Chris D. Bartels; Nash M. Borges; Arthur Kantor; Partha Lal; Lisa Yung; Ari Bezman; Stephen Dawson-Haggerty; Bronwyn Woods; et al. (ICASSP (4), 2007)

Object Category Recognition Using Probabilistic Fusion of Speech and Image Classifiers. - Kate Saenko; Trevor Darrell (MLMI, 2007)

Unsupervised Learning of Visual Sense Models for Polysemous Words. - Kate Saenko; Trevor Darrell (NIPS, 2008)

Filtering Abstract Senses From Image Search Results. - Kate Saenko; Trevor Darrell (NIPS, 2009)

Multistream Articulatory Feature-Based Models for Visual Speech Recognition. - Kate Saenko; Karen Livescu; James R. Glass; Trevor Darrell (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Adapting Visual Category Models to New Domains. - Kate Saenko; Brian Kulis; Mario Fritz; Trevor Darrell (ECCV (4), 2010)

Size Matters: Metric Visual Search Constraints from Monocular Metadata. - Mario Fritz; Kate Saenko; Trevor Darrell (NIPS, 2010)

What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. - Brian Kulis; Kate Saenko; Trevor Darrell (CVPR, 2011)

Learning object color models from multi-view constraints. - Trevor Owens; Kate Saenko; Ayan Chakrabarti; Ying Xiong; Todd E. Zickler; Trevor Darrell (CVPR, 2011)

The NBNN kernel. - Tinne Tuytelaars; Mario Fritz; Kate Saenko; Trevor Darrell (ICCV, 2011)

A category-level 3-D object dataset: Putting the Kinect to work. - Allison Janoch; Sergey Karayev; Yangqing Jia; Jonathan T. Barron; Mario Fritz; Kate Saenko; Trevor Darrell (ICCV Workshops, 2011)

Practical 3-D object detection using category and instance-level appearance models. - Kate Saenko; Sergey Karayev; Yangqing Jia; Alex Shyr; Allison Janoch; Jonathan Long; Mario Fritz; Trevor Darrell (IROS, 2011)

A combined pose, object, and feature model for action understanding. - Benjamin Packer; Kate Saenko; Daphne Koller (CVPR, 2012)

From pixels to physics: Probabilistic color de-rendering. - Ying Xiong; Kate Saenko; Trevor Darrell; Todd E. Zickler (CVPR, 2012)

Discovering Latent Domains for Multisource Domain Adaptation. - Judy Hoffman; Brian Kulis; Trevor Darrell; Kate Saenko (ECCV (2), 2012)

Generating Natural-Language Video Descriptions Using Text-Mined Knowledge. - Niveda Krishnamoorthy; Girish Malkarnenkar; Raymond J. Mooney; Kate Saenko; Sergio Guadarrama (AAAI, 2013)

Semi-supervised Domain Adaptation with Instance Constraints. - Jeff Donahue; Judy Hoffman; Erik Rodner; Kate Saenko; Trevor Darrell (CVPR, 2013)

YouTube2Text: Recognizing and Describing Arbitrary Activities Using Semantic Hierarchies and Zero-Shot Recognition. - Sergio Guadarrama; Niveda Krishnamoorthy; Girish Malkarnenkar; Subhashini Venugopalan; Raymond J. Mooney; Trevor Darrell; Kate Saenko (ICCV, 2013)

"Off the grid": Self-contained landmarks for improved indoor probabilistic localization. - Eric McCann; Mikhail S. Medvedev; Daniel J. Brooks; Kate Saenko (TePRA, 2013)

Towards Adapting ImageNet to Reality: Scalable Domain Adaptation with Implicit Low-rank Transformations. - Erik Rodner; Judy Hoffman; Jeff Donahue; Trevor Darrell; Kate Saenko (CoRR, 2013)

Efficient Learning of Domain-invariant Image Representations - Judy Hoffman; Erik Rodner; Jeff Donahue; Kate Saenko; Trevor Darrell (ICLR (Poster), 2013)

A Category-Level 3D Object Dataset: Putting the Kinect to Work. - Allison Janoch; Sergey Karayev; Yangqing Jia; Jonathan T. Barron; Mario Fritz; Kate Saenko; Trevor Darrell (Consumer Depth Cameras for Computer Vision, 2013)

From Virtual to Reality: Fast Adaptation of Virtual Object Detectors to Real Domains. - Baochen Sun; Kate Saenko (BMVC, 2014)

Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild. - Jesse Thomason; Subhashini Venugopalan; Sergio Guadarrama; Kate Saenko; Raymond J. Mooney (COLING, 2014)

Confidence-Rated Multiple Instance Boosting for Object Detection. - Karim Ali 002; Kate Saenko (CVPR, 2014)

Continuous Manifold Based Adaptation for Evolving Visual Domains. - Judy Hoffman; Trevor Darrell; Kate Saenko (CVPR, 2014)

Interactive adaptation of real-time object detectors. - Daniel Goehring; Judy Hoffman; Erik Rodner; Kate Saenko; Trevor Darrell (ICRA, 2014)

LSDA: Large Scale Detection through Adaptation. - Judy Hoffman; Sergio Guadarrama; Eric Tzeng; Ronghang Hu; Jeff Donahue; Ross B. Girshick; Trevor Darrell; Kate Saenko (NIPS, 2014)

Open-vocabulary Object Retrieval. - Sergio Guadarrama; Erik Rodner; Kate Saenko; Ning Zhang 014; Ryan Farrell; Jeff Donahue; Trevor Darrell (Robotics: Science and Systems, 2014)

LSDA: Large Scale Detection Through Adaptation. - Judy Hoffman; Sergio Guadarrama; Eric Tzeng; Jeff Donahue; Ross B. Girshick; Trevor Darrell; Kate Saenko (CoRR, 2014)

One-Shot Adaptation of Supervised Deep Convolutional Models. - Judy Hoffman; Eric Tzeng; Jeff Donahue; Yangqing Jia; Kate Saenko; Trevor Darrell (ICLR (Workshop Poster), 2014)

Exploring Invariances in Deep Convolutional Neural Networks Using Synthetic Images. - Xingchao Peng; Baochen Sun; Karim Ali 002; Kate Saenko (CoRR, 2014)

Deep Domain Confusion: Maximizing for Domain Invariance. - Eric Tzeng; Judy Hoffman; Ning Zhang 014; Kate Saenko; Trevor Darrell (CoRR, 2014)

Asymmetric and Category Invariant Feature Transformations for Domain Adaptation. - Judy Hoffman; Erik Rodner; Jeff Donahue; Brian Kulis; Kate Saenko (Int. J. Comput. Vis., 2014)

Modeling Radiometric Uncertainty for Vision with Tone-Mapped Color Images. - Ayan Chakrabarti; Ying Xiong; Baochen Sun; Trevor Darrell; Daniel Scharstein; Todd E. Zickler; Kate Saenko (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Subspace Distribution Alignment for Unsupervised Domain Adaptation. - Baochen Sun; Kate Saenko (BMVC, 2015)

Detector discovery in the wild: Joint multiple instance and representation learning. - Judy Hoffman; Deepak Pathak; Trevor Darrell; Kate Saenko (CVPR, 2015)

Spatial Semantic Regularisation for Large Scale Object Detection. - Damian Mrowca; Marcus Rohrbach; Judy Hoffman; Ronghang Hu; Kate Saenko; Trevor Darrell (ICCV, 2015)

Learning Deep Object Detectors from 3D Models. - Xingchao Peng; Baochen Sun; Karim Ali 002; Kate Saenko (ICCV, 2015)

Simultaneous Deep Transfer Across Domains and Tasks. - Eric Tzeng; Judy Hoffman; Trevor Darrell; Kate Saenko (ICCV, 2015)

Sequence to Sequence - Video to Text. - Subhashini Venugopalan; Marcus Rohrbach; Jeffrey Donahue; Raymond J. Mooney; Trevor Darrell; Kate Saenko (ICCV, 2015)

Translating Videos to Natural Language Using Deep Recurrent Neural Networks. - Subhashini Venugopalan; Huijuan Xu 001; Jeff Donahue; Marcus Rohrbach; Raymond J. Mooney; Kate Saenko (HLT-NAACL, 2015)

What Do Deep CNNs Learn About Objects? - Xingchao Peng; Baochen Sun; Karim Ali 002; Kate Saenko (ICLR (Workshop), 2015)

Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments. - Eric Tzeng; Coline Devin; Judy Hoffman; Chelsea Finn; Xingchao Peng; Sergey Levine; Kate Saenko; Trevor Darrell (CoRR, 2015)

A Multi-scale Multiple Instance Video Description Network. - Huijuan Xu 001; Subhashini Venugopalan; Vasili Ramanishka; Marcus Rohrbach; Kate Saenko (CoRR, 2015)

Return of Frustratingly Easy Domain Adaptation. - Baochen Sun; Jiashi Feng; Kate Saenko (AAAI, 2016)

Combining Texture and Shape Cues for Object Recognition with Minimal Supervision. - Xingchao Peng; Kate Saenko (ACCV (4), 2016)

MUTT: Metric Unit TesTing for Language Generation Tasks. - William Boag; Renan Campos; Kate Saenko; Anna Rumshisky (ACL (1), 2016)

Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data. - Lisa Anne Hendricks; Subhashini Venugopalan; Marcus Rohrbach; Raymond J. Mooney; Kate Saenko; Trevor Darrell (CVPR, 2016)

Natural Language Object Retrieval. - Ronghang Hu; Huazhe Xu; Marcus Rohrbach; Jiashi Feng; Kate Saenko; Trevor Darrell (CVPR, 2016)

Deep CORAL: Correlation Alignment for Deep Domain Adaptation. - Baochen Sun; Kate Saenko (ECCV Workshops (3), 2016)

Ask, Attend and Answer: Exploring Question-Guided Spatial Attention for Visual Question Answering. - Huijuan Xu 001; Kate Saenko (ECCV (7), 2016)

Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text. - Subhashini Venugopalan; Lisa Anne Hendricks; Raymond J. Mooney; Kate Saenko (EMNLP, 2016)

Fine-to-coarse knowledge transfer for low-res image classification. - Xingchao Peng; Judy Hoffman; Stella X. Yu; Kate Saenko (ICIP, 2016)

High precision grasp pose detection in dense clutter. - Marcus Gualtieri; Andreas ten Pas; Kate Saenko; Robert Platt Jr. 001 (IROS, 2016)

Vision and Language Integration Meets Multimedia Fusion: Proceedings of ACM Multimedia 2016 Workshop. - Marie-Francine Moens; Katerina Pastra; Kate Saenko; Tinne Tuytelaars (ACM Multimedia, 2016)

Multimodal Video Description. - Vasili Ramanishka; Abir Das; Dong Huk Park; Subhashini Venugopalan; Lisa Anne Hendricks; Marcus Rohrbach; Kate Saenko (ACM Multimedia, 2016)

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints. - Eric Tzeng; Coline Devin; Judy Hoffman; Chelsea Finn; Pieter Abbeel; Sergey Levine; Kate Saenko; Trevor Darrell (WAFR, 2016)

Correlation Alignment for Unsupervised Domain Adaptation. - Baochen Sun; Jiashi Feng; Kate Saenko (CoRR, 2016)

Understanding object descriptions in robotics by open-vocabulary object retrieval and detection. - Sergio Guadarrama; Erik Rodner; Kate Saenko; Trevor Darrell (Int. J. Robotics Res., 2016)

Large Scale Visual Recognition through Adaptation using Joint Representation and Multiple Instance Learning. - Judy Hoffman; Deepak Pathak; Eric Tzeng; Jonathan Long; Sergio Guadarrama; Trevor Darrell; Kate Saenko (J. Mach. Learn. Res., 2016)

Learning a visuomotor controller for real world robotic grasping using simulated depth images. - Ulrich Viereck; Andreas ten Pas; Kate Saenko; Robert Platt Jr. 001 (CoRL, 2017)

Modeling Relationships in Referential Expressions with Compositional Modular Networks. - Ronghang Hu; Marcus Rohrbach; Jacob Andreas; Trevor Darrell; Kate Saenko (CVPR, 2017)

Top-Down Visual Saliency Guided by Captions. - Vasili Ramanishka; Abir Das; Jianming Zhang 001; Kate Saenko (CVPR, 2017)

Adversarial Discriminative Domain Adaptation. - Eric Tzeng; Judy Hoffman; Kate Saenko; Trevor Darrell (CVPR, 2017)

Captioning Images with Diverse Objects. - Subhashini Venugopalan; Lisa Anne Hendricks; Marcus Rohrbach; Raymond J. Mooney; Trevor Darrell; Kate Saenko (CVPR, 2017)

Learning to Reason: End-to-End Module Networks for Visual Question Answering. - Ronghang Hu; Jacob Andreas; Marcus Rohrbach; Trevor Darrell; Kate Saenko (ICCV, 2017)

R-C3D: Region Convolutional 3D Network for Temporal Activity Detection. - Huijuan Xu 001; Abir Das; Kate Saenko (ICCV, 2017)

Ground2sky label transfer for fine-grained aerial car recognition. - Baochen Sun; Xingchao Peng; Stella X. Yu; Kate Saenko (ICIP, 2017)

Adversarial Discriminative Domain Adaptation (workshop extended abstract). - Eric Tzeng; Judy Hoffman; Kate Saenko; Trevor Darrell (ICLR (Workshop), 2017)

Synthetic to Real Adaptation with Deep Generative Correlation Alignment Networks. - Xingchao Peng; Kate Saenko (CoRR, 2017)

Learning a visuomotor controller for real world robotic grasping using easily simulated depth images. - Ulrich Viereck; Andreas ten Pas; Kate Saenko; Robert Platt Jr. 001 (CoRR, 2017)

VisDA: The Visual Domain Adaptation Challenge. - Xingchao Peng; Ben Usman; Neela Kaushik; Judy Hoffman; Dequan Wang; Kate Saenko (CoRR, 2017)

Hierarchical Actor-Critic. - Andrew Levy; Robert Platt Jr. 001; Kate Saenko (CoRR, 2017)

Guest Editorial: Image and Language Understanding. - Margaret Mitchell; John C. Platt; Kate Saenko (Int. J. Comput. Vis., 2017)

Grasp Pose Detection in Point Clouds. - Andreas ten Pas; Marcus Gualtieri; Kate Saenko; Robert Platt Jr. 001 (Int. J. Robotics Res., 2017)

Long-Term Recurrent Convolutional Networks for Visual Recognition and Description. - Jeff Donahue; Lisa Anne Hendricks; Marcus Rohrbach; Subhashini Venugopalan; Sergio Guadarrama; Kate Saenko; Trevor Darrell (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Simultaneous Deep Transfer Across Domains and Tasks. - Judy Hoffman; Eric Tzeng; Trevor Darrell; Kate Saenko (Domain Adaptation in Computer Vision Applications, 2017)

Correlation Alignment for Unsupervised Domain Adaptation. - Baochen Sun; Jiashi Feng; Kate Saenko (Domain Adaptation in Computer Vision Applications, 2017)

RISE: Randomized Input Sampling for Explanation of Black-box Models. - Vitali Petsiuk; Abir Das; Kate Saenko (BMVC, 2018)

VisDA: A Synthetic-to-Real Benchmark for Visual Domain Adaptation. - Xingchao Peng; Ben Usman; Neela Kaushik; Dequan Wang; Judy Hoffman; Kate Saenko (CVPR Workshops, 2018)

Toward Driving Scene Understanding: A Dataset for Learning Driver Behavior and Causal Reasoning. - Vasili Ramanishka; Yi-Ting Chen 001; Teruhisa Misu; Kate Saenko (CVPR, 2018)

Women Also Snowboard: Overcoming Bias in Captioning Models. - Lisa Anne Hendricks; Kaylee Burns; Kate Saenko; Trevor Darrell; Anna Rohrbach (ECCV (3), 2018)

Explainable Neural Computation via Stack Neural Module Networks. - Ronghang Hu; Jacob Andreas; Trevor Darrell; Kate Saenko (ECCV (7), 2018)

Object Hallucination in Image Captioning. - Anna Rohrbach; Lisa Anne Hendricks; Kaylee Burns; Trevor Darrell; Kate Saenko (EMNLP, 2018)

Adversarial Dropout Regularization. - Kuniaki Saito; Yoshitaka Ushiku; Tatsuya Harada; Kate Saenko (ICLR (Poster), 2018)

Stable Distribution Alignment Using the Dual of the Adversarial Distance. - Ben Usman; Kate Saenko; Brian Kulis (ICLR (Workshop), 2018)

CyCADA: Cycle-Consistent Adversarial Domain Adaptation. - Judy Hoffman; Eric Tzeng; Taesung Park; Jun-Yan Zhu; Phillip Isola; Kate Saenko; Alexei A. Efros; Trevor Darrell (ICML, 2018)

Adapting Control Policies from Simulation to Reality Using a Pairwise Loss. - Ulrich Viereck; Xingchao Peng; Kate Saenko; Robert Platt Jr. 001 (ISER, 2018)

Speaker-Follower Models for Vision-and-Language Navigation. - Daniel Fried; Ronghang Hu; Volkan Cirik; Anna Rohrbach; Jacob Andreas; Louis-Philippe Morency; Taylor Berg-Kirkpatrick; Kate Saenko; Dan Klein 001; Trevor Darrell (NeurIPS, 2018)

Synthetic to Real Adaptation with Generative Correlation Alignment Networks. - Xingchao Peng; Kate Saenko (WACV, 2018)

Contextual Multi-Scale Region Convolutional 3D Network for Activity Detection. - Yancheng Bai; Huijuan Xu 001; Kate Saenko; Bernard Ghanem (CoRR, 2018)

Text-to-Clip Video Retrieval with Early Fusion and Re-Captioning. - Huijuan Xu 001; Kun He 003; Leonid Sigal; Stan Sclaroff; Kate Saenko (CoRR, 2018)

Unsupervised Video-to-Video Translation. - Dina Bashkirova; Ben Usman; Kate Saenko (CoRR, 2018)

Syn2Real: A New Benchmark forSynthetic-to-Real Visual Domain Adaptation. - Xingchao Peng; Ben Usman; Kuniaki Saito; Neela Kaushik; Judy Hoffman; Kate Saenko (CoRR, 2018)

Women also Snowboard: Overcoming Bias in Captioning Models (Extended Abstract). - Lisa Anne Hendricks; Kaylee Burns; Kate Saenko; Trevor Darrell; Anna Rohrbach (CoRR, 2018)

Adapting control policies from simulation to reality using a pairwise loss. - Ulrich Viereck; Kate Saenko; Robert Platt Jr. 001 (CoRR, 2018)

Open-vocabulary Phrase Detection. - Bryan A. Plummer; Kevin J. Shih; Yichen Li; Ke Xu; Svetlana Lazebnik; Stan Sclaroff; Kate Saenko (CoRR, 2018)

SPLAT: Semantic Pixel-Level Adaptation Transforms for Detection. - Eric Tzeng; Kaylee Burns; Kate Saenko; Trevor Darrell (CoRR, 2018)

A Two-Stream Variational Adversarial Network for Video Generation. - Ximeng Sun; Huijuan Xu 001; Kate Saenko (CoRR, 2018)

Similarity R-C3D for Few-shot Temporal Activity Detection. - Huijuan Xu 001; Bingyi Kang; Ximeng Sun; Jiashi Feng; Kate Saenko; Trevor Darrell (CoRR, 2018)

Vision and Language Integration Meets Multimedia Fusion. - Marie-Francine Moens; Katerina Pastra; Kate Saenko; Tinne Tuytelaars (IEEE Multim., 2018)

Multilevel Language and Vision Integration for Text-to-Clip Retrieval. - Huijuan Xu 001; Kun He 003; Bryan A. Plummer; Leonid Sigal; Stan Sclaroff; Kate Saenko (AAAI, 2019)

Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation. - Ronghang Hu; Daniel Fried; Anna Rohrbach; Dan Klein 001; Trevor Darrell; Kate Saenko (ACL (1), 2019)

Guided Zoom: Questioning Network Evidence for Fine-grained Classification. - Sarah Adel Bargal; Andrea Zunino; Vitali Petsiuk; Jianming Zhang 001; Kate Saenko; Vittorio Murino; Stan Sclaroff (BMVC, 2019)

Are CNN Predictions based on Reasonable Evidence? - Sarah Adel Bargal; Andrea Zunino; Vitali Petsiuk; Jianming Zhang 001; Kate Saenko; Vittorio Murino; Stan Sclaroff (CVPR Workshops, 2019)

Strong-Weak Distribution Alignment for Adaptive Object Detection. - Kuniaki Saito; Yoshitaka Ushiku; Tatsuya Harada; Kate Saenko (CVPR, 2019)

Language Features Matter: Effective Language Representations for Vision-Language Tasks. - Andrea Burns; Reuben Tan; Kate Saenko; Stan Sclaroff; Bryan A. Plummer (ICCV, 2019)

Language-Conditioned Graph Networks for Relational Reasoning. - Ronghang Hu; Anna Rohrbach; Trevor Darrell; Kate Saenko (ICCV, 2019)

Moment Matching for Multi-Source Domain Adaptation. - Xingchao Peng; Qinxun Bai; Xide Xia; Zijun Huang; Kate Saenko; Bo Wang 044 (ICCV, 2019)

Semi-Supervised Domain Adaptation via Minimax Entropy. - Kuniaki Saito; Donghyun Kim 006; Stan Sclaroff; Trevor Darrell; Kate Saenko (ICCV, 2019)

Learning Similarity Conditions Without Explicit Supervision. - Reuben Tan; Mariya I. Vasileva; Kate Saenko; Bryan A. Plummer (ICCV, 2019)

PuppetGAN: Cross-Domain Image Manipulation by Demonstration. - Ben Usman; Nick Dufour; Kate Saenko; Chris Bregler (ICCV, 2019)

Learning Multi-Level Hierarchies with Hindsight. - Andrew Levy; George Dimitri Konidaris; Robert Platt Jr. 001; Kate Saenko (ICLR (Poster), 2019)

Domain Agnostic Learning with Disentangled Representations. - Xingchao Peng; Zijun Huang; Ximeng Sun; Kate Saenko (ICML, 2019)

Adversarial Self-Defense for Cycle-Consistent GANs. - Dina Bashkirova; Ben Usman; Kate Saenko (NeurIPS, 2019)

Joint Event Detection and Description in Continuous Video Streams. - Huijuan Xu 001; Boyang Li 001; Vasili Ramanishka; Leonid Sigal; Kate Saenko (WACV Workshops, 2019)

PuppetGAN: Transferring Disentangled Properties from Synthetic to Real Images. - Ben Usman; Nick Dufour; Kate Saenko; Chris Bregler (CoRR, 2019)

Weakly-supervised Compositional FeatureAggregation for Few-shot Recognition. - Ping Hu 001; Ximeng Sun; Kate Saenko; Stan Sclaroff (CoRR, 2019)

wMAN: Weakly-supervised Moment Alignment Network for Text-based Video Segment Retrieval. - Reuben Tan; Huijuan Xu 001; Kate Saenko; Bryan A. Plummer (CoRR, 2019)

Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment. - Shuhan Tan; Xingchao Peng; Kate Saenko (CoRR, 2019)

Two-Stream Region Convolutional 3D Network for Temporal Activity Detection. - Huijuan Xu 001; Abir Das; Kate Saenko (IEEE Trans. Pattern Anal. Mach. Intell., 2019)

MULE: Multimodal Universal Language Embedding. - Donghyun Kim 006; Kuniaki Saito; Kate Saenko; Stan Sclaroff; Bryan A. Plummer (AAAI, 2020)

Learning to Scale Multilingual Representations for Vision-Language Tasks. - Andrea Burns; Donghyun Kim 006; Derry Wijaya; Kate Saenko; Bryan A. Plummer (ECCV (4), 2020)

A Broader Study of Cross-Domain Few-Shot Learning. - Yunhui Guo; Noel Codella; Leonid Karlinsky; James V. Codella; John R. Smith; Kate Saenko; Tajana Rosing; Rogério Feris (ECCV (27), 2020)

AR-Net: Adaptive Frame Resolution for Efficient Action Recognition. - Yue Meng; Chung-Ching Lin; Rameswar Panda; Prasanna Sattigeri; Leonid Karlinsky; Aude Oliva; Kate Saenko; Rogério Feris (ECCV (7), 2020)

Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation. - Xingchao Peng; Yichen Li; Kate Saenko (ECCV (6), 2020)

Why Do These Match? Explaining the Behavior of Image Similarity Models. - Bryan A. Plummer; Mariya I. Vasileva; Vitali Petsiuk; Kate Saenko; David A. Forsyth (ECCV (11), 2020)

COCO-FUNIT: Few-Shot Unsupervised Image Translation with a Content Conditioned Style Encoder. - Kuniaki Saito; Kate Saenko; Ming-Yu Liu 001 (ECCV (3), 2020)

Class-Imbalanced Domain Adaptation: An Empirical Odyssey. - Shuhan Tan; Xingchao Peng; Kate Saenko (ECCV Workshops (1), 2020)

Detecting Cross-Modal Inconsistency to Defend Against Neural Fake News. - Reuben Tan; Bryan A. Plummer; Kate Saenko (EMNLP (1), 2020)

Federated Adversarial Domain Adaptation. - Xingchao Peng; Zijun Huang; Yizhe Zhu; Kate Saenko (ICLR, 2020)

Beyond the Visual Analysis of Deep Model Saliency. - Sarah Adel Bargal; Andrea Zunino; Vitali Petsiuk; Jianming Zhang 001; Vittorio Murino; Stan Sclaroff; Kate Saenko (xxAI@ICML, 2020)

Learning Visual Servo Policies via Planner Cloning. - Ulrich Viereck; Kate Saenko; Robert Platt Jr. 001 (ISER, 2020)

Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation. - Ping Hu 001; Stan Sclaroff; Kate Saenko (NeurIPS, 2020)

Universal Domain Adaptation through Self Supervision. - Kuniaki Saito; Donghyun Kim 006; Stan Sclaroff; Kate Saenko (NeurIPS, 2020)

Auxiliary Task Reweighting for Minimum-data Learning. - Baifeng Shi; Judy Hoffman; Kate Saenko; Trevor Darrell; Huijuan Xu 001 (NeurIPS, 2020)

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning. - Ximeng Sun; Rameswar Panda; Rogério Feris; Kate Saenko (NeurIPS, 2020)

Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment. - Ben Usman; Avneesh Sud; Nick Dufour; Kate Saenko (NeurIPS, 2020)

DIPNet: Dynamic Identity Propagation Network for Video Object Segmentation. - Ping Hu 001; Jun Liu 036; Gang Wang 012; Vitaly Ablavsky; Kate Saenko; Stan Sclaroff (WACV, 2020)

TwoStreamVAN: Improving Motion Modeling in Video Generation. - Ximeng Sun; Huijuan Xu 001; Kate Saenko (WACV, 2020)

Cross-domain Self-supervised Learning for Domain Adaptation with Few Source Labels. - Donghyun Kim 006; Kuniaki Saito; Tae-Hyun Oh; Bryan A. Plummer; Stan Sclaroff; Kate Saenko (CoRR, 2020)

Revisiting Few-shot Activity Detection with Class Similarity Control. - Huijuan Xu 001; Ximeng Sun; Eric Tzeng; Abir Das; Kate Saenko; Trevor Darrell (CoRR, 2020)

Spatio-Temporal Action Detection with Multi-Object Interaction. - Huijuan Xu 001; Lizhi Yang; Stan Sclaroff; Kate Saenko; Trevor Darrell (CoRR, 2020)

Shapeshifter Networks: Cross-layer Parameter Sharing for Scalable and Effective Deep Learning. - Bryan A. Plummer; Nikoli Dryden; Julius Frost; Torsten Hoefler; Kate Saenko (CoRR, 2020)

Self-supervised Visual Attribute Learning for Fashion Compatibility. - Donghyun Kim 006; Kuniaki Saito; Kate Saenko; Stan Sclaroff; Bryan A. Plummer (CoRR, 2020)

Learning from Lexical Perturbations for Consistent Visual Question Answering. - Spencer Whitehead; Hui Wu 009; Yi Ren Fung 001; Heng Ji 001; Rogério Schmidt Feris; Kate Saenko (CoRR, 2020)

Surprisingly Simple Semi-Supervised Domain Adaptation with Pretraining and Consistency. - Samarth Mishra; Kate Saenko; Venkatesh Saligrama (BMVC, 2021)

Honey. I Shrunk The Actor: A Case Study on Preserving Performance with Smaller Actors in Actor-Critic RL. - Siddharth Mysore; Bassel El Mabsout; Renato Mancuso 001; Kate Saenko (CoG, 2021)

Fine-Grained Angular Contrastive Learning With Coarse Labels. - Guy Bukchin; Eli Schwartz; Kate Saenko; Ori Shahar; Rogério Feris; Raja Giryes; Leonid Karlinsky (CVPR, 2021)

Black-Box Explanation of Object Detectors via Saliency Maps. - Vitali Petsiuk; Rajiv Jain; Varun Manjunatha; Vlad I. Morariu; Ashutosh Mehra 002; Vicente Ordonez; Kate Saenko (CVPR, 2021)

Semi-Supervised Action Recognition With Temporal Contrastive Learning. - Ankit Singh; Omprakash Chakraborty; Ashutosh Varshney; Rameswar Panda; Rogério Feris; Kate Saenko; Abir Das (CVPR, 2021)

Separating Skills and Concepts for Novel Visual Question Answering. - Spencer Whitehead; Hui Wu 009; Heng Ji 001; Rogério Feris; Kate Saenko (CVPR, 2021)

Explainable Deep Classification Models for Domain Generalization. - Andrea Zunino; Sarah Adel Bargal; Riccardo Volpi; Mehrnoosh Sameki; Jianming Zhang 001; Stan Sclaroff; Vittorio Murino; Kate Saenko (CVPR Workshops, 2021)

Detector-Free Weakly Supervised Grounding by Separation. - Assaf Arbelle; Sivan Doveh; Amit Alfassy; Joseph Shtok; Guy Lev; Eli Schwartz; Hilde Kuehne; Hila Barak Levi; Prasanna Sattigeri; Rameswar Panda; Chun-Fu Chen 001; Alex M. Bronstein; et al. (ICCV, 2021)

CDS: Cross-Domain Self-supervised Pre-training. - Donghyun Kim 006; Kuniaki Saito; Tae-Hyun Oh; Bryan A. Plummer; Stan Sclaroff; Kate Saenko (ICCV, 2021)

Learning Cross-Modal Contrastive Features for Video Domain Adaptation. - Donghyun Kim 006; Yi-Hsuan Tsai; Bingbing Zhuang; Xiang Yu 002; Stan Sclaroff; Kate Saenko; Manmohan Chandraker (ICCV, 2021)

AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition. - Rameswar Panda; Chun-Fu (Richard) Chen; Quanfu Fan; Ximeng Sun; Kate Saenko; Aude Oliva; Rogério Feris (ICCV, 2021)

Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings. - Viraj Prabhu; Arjun Chandrasekaran; Kate Saenko; Judy Hoffman (ICCV, 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)

OVANet: One-vs-All Network for Universal Domain Adaptation. - Kuniaki Saito; Kate Saenko (ICCV, 2021)

Temporal Action Detection with Multi-level Supervision. - Baifeng Shi; Qi Dai 001; Judy Hoffman; Kate Saenko; Trevor Darrell; Huijuan Xu 001 (ICCV, 2021)

Dynamic Network Quantization for Efficient Video Inference. - Ximeng Sun; Rameswar Panda; Chun-Fu (Richard) Chen; Aude Oliva; Rogério Feris; Kate Saenko (ICCV, 2021)

Self-supervised Visual Attribute Learning for Fashion Compatibility. - Donghyun Kim 006; Kuniaki Saito; Samarth Mishra; Stan Sclaroff; Kate Saenko; Bryan A. Plummer (ICCVW, 2021)

AdaFuse: Adaptive Temporal Fusion Network for Efficient Action Recognition. - Yue Meng; Rameswar Panda; Chung-Ching Lin; Prasanna Sattigeri; Leonid Karlinsky; Kate Saenko; Aude Oliva; Rogério Feris (ICLR, 2021)

VA-RED2: Video Adaptive Redundancy Reduction. - Bowen Pan; Rameswar Panda; Camilo Luciano Fosco; Chung-Ching Lin; Alex J. Andonian; Yue Meng; Kate Saenko; Aude Oliva; Rogério Feris (ICLR, 2021)

Regularizing Action Policies for Smooth Control with Reinforcement Learning. - Siddharth Mysore; Bassel Mabsout; Renato Mancuso 001; Kate Saenko (ICRA, 2021)

Weakly Supervised Domain Adaptation using Super-pixel labeling for Semantic Segmentation. - Masaki Yamazaki; Xingchao Peng; Kuniaki Saito; Ping Hu 001; Kate Saenko; Yasuhiro Taniguchi (MVA, 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)

Contrast and Mix: Temporal Contrastive Video Domain Adaptation with Background Mixing. - Aadarsh Sahoo; Rutav Shah; Rameswar Panda; Kate Saenko; Abir Das (NeurIPS, 2021)

OpenMatch: Open-Set Semi-supervised Learning with Open-set Consistency Regularization. - Kuniaki Saito; Donghyun Kim 006; Kate Saenko (NeurIPS, 2021)

Look at What I'm Doing: Self-Supervised Spatial Grounding of Narrations in Instructional Videos. - Reuben Tan; Bryan A. Plummer; Kate Saenko; Hailin Jin; Bryan C. Russell (NeurIPS, 2021)

LoGAN: Latent Graph Co-Attention Network for Weakly-Supervised Video Moment Retrieval. - Reuben Tan; Huijuan Xu 001; Kate Saenko; Bryan A. Plummer (WACV, 2021)

VA-RED2: Video Adaptive Redundancy Reduction. - Bowen Pan; Rameswar Panda; Camilo Fosco; Chung-Ching Lin; Alex Andonian; Yue Meng; Kate Saenko; Aude Oliva; Rogério Feris (CoRR, 2021)

Good Actors can come in Smaller Sizes: A Case Study on the Value of Actor-Critic Asymmetry. - Siddharth Mysore; Bassel Mabsout; Renato Mancuso 001; Kate Saenko (CoRR, 2021)

All at Once Network Quantization via Collaborative Knowledge Transfer. - Ximeng Sun; Rameswar Panda; Chun-Fu Chen 001; Naigang Wang; Bowen Pan; Kailash Gopalakrishnan; Aude Oliva; Rogério Feris; Kate Saenko (CoRR, 2021)

Mobile App Tasks with Iterative Feedback (MoTIF): Addressing Task Feasibility in Interactive Visual Environments. - Andrea Burns; Deniz Arsan; Sanjna Agrawal; Ranjitha Kumar; Kate Saenko; Bryan A. Plummer (CoRR, 2021)

OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers. - Kuniaki Saito; Donghyun Kim 006; Kate Saenko (CoRR, 2021)

ZeroWaste Dataset: Towards Automated Waste Recycling. - Dina Bashkirova; Ziliang Zhu; James Akl; Fadi M. Alladkani; Ping Hu 001; Vitaly Ablavsky; Berk Çalli; Sarah Adel Bargal; Kate Saenko (CoRR, 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)

Disentangled Unsupervised Image Translation via Restricted Information Flow. - Ben Usman; Dina Bashkirova; Kate Saenko (CoRR, 2021)

Guided Zoom: Zooming into Network Evidence to Refine Fine-Grained Model Decisions. - Sarah Adel Bargal; Andrea Zunino; Vitali Petsiuk; Jianming Zhang 001; Kate Saenko; Vittorio Murino; Stan Sclaroff (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Real-Time Semantic Segmentation With Fast Attention. - Ping Hu 001; Federico Perazzi; Fabian Caba Heilbron; Oliver Wang; Zhe Lin 001; Kate Saenko; Stan Sclaroff (IEEE Robotics Autom. Lett., 2021)

How to Train Your Quadrotor: A Framework for Consistently Smooth and Responsive Flight Control via Reinforcement Learning. - Siddharth Mysore; Bassel Mabsout; Kate Saenko; Renato Mancuso 001 (ACM Trans. Cyber Phys. Syst., 2021)

ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes. - Dina Bashkirova; Mohamed Abdelfattah; Ziliang Zhu; James Akl; Fadi M. Alladkani; Ping Hu 001; Vitaly Ablavsky; Berk Çalli; Sarah Adel Bargal; Kate Saenko (CVPR, 2022)

Unsupervised Domain Generalization by Learning a Bridge Across Domains. - Sivan Harary; Eli Schwartz; Assaf Arbelle; Peter W. J. Staar; Shady Abu-Hussein; Elad Amrani; Roei Herzig; Amit Alfassy; Raja Giryes; Hilde Kuehne; Dina Katabi; Kate Saenko; et al. (CVPR, 2022)

Many-to-many Splatting for Efficient Video Frame Interpolation. - Ping Hu 001; Simon Niklaus; Stan Sclaroff; Kate Saenko (CVPR, 2022)

Task2Sim: Towards Effective Pre-training and Transfer from Synthetic Data. - Samarth Mishra; Rameswar Panda; Cheng Perng Phoo; Chun-Fu Richard Chen; Leonid Karlinsky; Kate Saenko; Venkatesh Saligrama; Rogério Schmidt Feris (CVPR, 2022)

MetaPose: Fast 3D Pose from Multiple Views without 3D Supervision. - Ben Usman; Andrea Tagliasacchi; Kate Saenko; Avneesh Sud (CVPR, 2022)

A Dataset for Interactive Vision-Language Navigation with Unknown Command Feasibility. - Andrea Burns; Deniz Arsan; Sanjna Agrawal; Ranjitha Kumar; Kate Saenko; Bryan A. Plummer (ECCV (8), 2022)

The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning. - Jack Hessel; Jena D. Hwang; Jae Sung Park; Rowan Zellers; Chandra Bhagavatula; Anna Rohrbach; Kate Saenko; Yejin Choi 001 (ECCV (36), 2022)

A Unified Framework for Domain Adaptive Pose Estimation. - Donghyun Kim 006; Kaihong Wang; Kate Saenko; Margrit Betke; Stan Sclaroff (ECCV (33), 2022)

A Broad Study of Pre-training for Domain Generalization and Adaptation. - Donghyun Kim 006; Kaihong Wang; Stan Sclaroff; Kate Saenko (ECCV (33), 2022)

Learning to Detect Every Thing in an Open World. - Kuniaki Saito; Ping Hu 001; Trevor Darrell; Kate Saenko (ECCV (24), 2022)

NewsStories: Illustrating Articles with Visual Summaries. - Reuben Tan; Bryan A. Plummer; Kate Saenko; J. P. Lewis 001; Avneesh Sud; Thomas Leung (ECCV (36), 2022)

Multi-Critic Actor Learning: Teaching RL Policies to Act with Style. - Siddharth Mysore; George Cheng; Yunqi Zhao; Kate Saenko; Meng Wu (ICLR, 2022)

Neural Parameter Allocation Search. - Bryan A. Plummer; Nikoli Dryden; Julius Frost; Torsten Hoefler; Kate Saenko (ICLR, 2022)

Extending the WILDS Benchmark for Unsupervised Adaptation. - Shiori Sagawa; Pang Wei Koh; Tony Lee; Irena Gao; Sang Michael Xie; Kendrick Shen; Ananya Kumar; Weihua Hu; Michihiro Yasunaga; Henrik Marklund; Sara Beery; Etienne David; et al. (ICLR, 2022)

FETA: Towards Specializing Foundational Models for Expert Task Applications. - Amit Alfassy; Assaf Arbelle; Oshri Halimi; Sivan Harary; Roei Herzig; Eli Schwartz; Rameswar Panda; Michele Dolfi; Christoph Auer; Peter W. J. Staar; Kate Saenko; Rogério Feris; et al. (NeurIPS, 2022)

How Transferable are Video Representations Based on Synthetic Data? - Yo-whan Kim; Samarth Mishra; SouYoung Jin; Rameswar Panda; Hilde Kuehne; Leonid Karlinsky; Venkatesh Saligrama; Kate Saenko; Aude Oliva; Rogério Feris (NeurIPS, 2022)

Finding Differences Between Transformers and ConvNets Using Counterfactual Simulation Testing. - Nataniel Ruiz; Sarah A. Bargal; Cihang Xie; Kate Saenko; Stan Sclaroff (NeurIPS, 2022)

DualCoOp: Fast Adaptation to Multi-Label Recognition with Limited Annotations. - Ximeng Sun; Ping Hu 001; Kate Saenko (NeurIPS, 2022)

Evaluation of Correctness in Unsupervised Many-to-Many Image Translation. - Dina Bashkirova; Ben Usman; Kate Saenko (WACV, 2022)

Explaining Reinforcement Learning Policies through Counterfactual Trajectories. - Julius Frost; Olivia Watkins; Eric Weiner; Pieter Abbeel; Trevor Darrell; Bryan A. Plummer; Kate Saenko (CoRR, 2022)

Interactive Mobile App Navigation with Uncertain or Under-specified Natural Language Commands. - Andrea Burns; Deniz Arsan; Sanjna Agrawal; Ranjitha Kumar; Kate Saenko; Bryan A. Plummer (CoRR, 2022)

Temporal Relevance Analysis for Video Action Models. - Quanfu Fan; Donghyun Kim 006; Chun-Fu Chen 001; Stan Sclaroff; Kate Saenko; Sarah Adel Bargal (CoRR, 2022)

FETA: Towards Specializing Foundation Models for Expert Task Applications. - Amit Alfassy; Assaf Arbelle; Oshri Halimi; Sivan Harary; Roei Herzig; Eli Schwartz; Rameswar Panda; Michele Dolfi; Christoph Auer; Kate Saenko; Peter W. J. Staar; Rogério Feris; et al. (CoRR, 2022)

Human Evaluation of Text-to-Image Models on a Multi-Task Benchmark. - Vitali Petsiuk; Alexander E. Siemenn; Saisamrit Surbehera; Zad Chin; Keith Tyser; Gregory Hunter; Arvind Raghavan; Yann Hicke; Bryan A. Plummer; Ori Kerret; Tonio Buonassisi; Kate Saenko; et al. (CoRR, 2022)

Exploring Consistency in Cross-Domain Transformer for Domain Adaptive Semantic Segmentation. - Kaihong Wang; Donghyun Kim 006; Rogério Feris; Kate Saenko; Margrit Betke (CoRR, 2022)

Ani-GIFs: A benchmark dataset for domain generalization of action recognition from GIFs. - Shoumik Sovan Majumdar; Shubhangi Jain; Isidora Chara Tourni; Arsenii Mustafin; Diala Lteif; Stan Sclaroff; Kate Saenko; Sarah Adel Bargal (Frontiers Comput. Sci., 2022)

Revisiting Image-Language Networks for Open-Ended Phrase Detection. - Bryan A. Plummer; Kevin J. Shih; Yichen Li; Ke Xu; Svetlana Lazebnik; Stan Sclaroff; Kate Saenko (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Leveraging Geometric Structure for Label-Efficient Semi-Supervised Scene Segmentation. - Ping Hu 001; Stan Sclaroff; Kate Saenko (IEEE Trans. Image Process., 2022)

MaskSketch: Unpaired Structure-guided Masked Image Generation. - Dina Bashkirova; José Lezama; Kihyuk Sohn; Kate Saenko; Irfan Essa (CVPR, 2023)

Bias Mimicking: A Simple Sampling Approach for Bias Mitigation. - Maan Qraitem; Kate Saenko; Bryan A. Plummer (CVPR, 2023)

Prefix Conditioning Unifies Language and Label Supervision. - Kuniaki Saito; Kihyuk Sohn; Xiang Zhang; Chun-Liang Li; Chen-Yu Lee; Kate Saenko; Tomas Pfister (CVPR, 2023)

Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. - Kuniaki Saito; Kihyuk Sohn; Xiang Zhang; Chun-Liang Li; Chen-Yu Lee; Kate Saenko; Tomas Pfister (CVPR, 2023)

Language-Guided Audio-Visual Source Separation via Trimodal Consistency. - Reuben Tan; Arijit Ray; Andrea Burns; Bryan A. Plummer; Justin Salamon; Oriol Nieto; Bryan C. Russell; Kate Saenko (CVPR, 2023)

A Suite of Generative Tasks for Multi-Level Multimodal Webpage Understanding. - Andrea Burns; Krishna Srinivasan; Joshua Ainslie; Geoff Brown; Bryan A. Plummer; Kate Saenko; Jianmo Ni; Mandy Guo (EMNLP, 2023)

DIME-FM : DIstilling Multimodal and Efficient Foundation Models. - Ximeng Sun; Pengchuan Zhang; Peizhao Zhang; Hardik Shah; Kate Saenko; Xide Xia (ICCV, 2023)

Cola: A Benchmark for Compositional Text-to-image Retrieval. - Arijit Ray; Filip Radenovic; Abhimanyu Dubey; Bryan A. Plummer; Ranjay Krishna; Kate Saenko (NeurIPS, 2023)

Select, Label, and Mix: Learning Discriminative Invariant Feature Representations for Partial Domain Adaptation. - Aadarsh Sahoo; Rameswar Panda; Rogério Feris; Kate Saenko; Abir Das (WACV, 2023)

RIFT: Disentangled Unsupervised Image Translation via Restricted Information Flow. - Ben Usman; Dina Bashkirova; Kate Saenko (WACV, 2023)

The SwaNNFlight System: On-the-Fly Sim-to-Real Adaptation via Anchored Learning. - Bassel El Mabsout; Shahin Roozkhosh; Siddharth Mysore; Kate Saenko; Renato Mancuso 001 (CoRR, 2023)

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

COLA: How to adapt vision-language models to Compose Objects Localized with Attributes? - Arijit Ray; Filip Radenovic; Abhimanyu Dubey; Bryan A. Plummer; Ranjay Krishna; Kate Saenko (CoRR, 2023)

WikiWeb2M: A Page-Level Multimodal Wikipedia Dataset. - Andrea Burns; Krishna Srinivasan; Joshua Ainslie; Geoff Brown; Bryan A. Plummer; Kate Saenko; Jianmo Ni; Mandy Guo (CoRR, 2023)

Hardwiring ViT Patch Selectivity into CNNs using Patch Mixing. - Ariel N. Lee; Sarah Adel Bargal; Janavi Kasera; Stan Sclaroff; Kate Saenko; Nataniel Ruiz (CoRR, 2023)

Multiscale Video Pretraining for Long-Term Activity Forecasting. - Reuben Tan; Matthias De Lange; Michael L. Iuzzolino; Bryan A. Plummer; Kate Saenko; Karl Ridgeway; Lorenzo Torresani (CoRR, 2023)

From Fake to Real (FFR): A two-stage training pipeline for mitigating spurious correlations with synthetic data. - Maan Qraitem; Kate Saenko; Bryan A. Plummer (CoRR, 2023)

Label Budget Allocation in Multi-Task Learning. - Ximeng Sun; Kihyuk Sohn; Kate Saenko; Clayton Mellina; Xiao Bian (CoRR, 2023)

Socratis: Are large multimodal models emotionally aware? - Katherine Deng; Arijit Ray; Reuben Tan; Saadia Gabriel; Bryan A. Plummer; Kate Saenko (CoRR, 2023)

Lasagna: Layered Score Distillation for Disentangled Object Relighting. - Dina Bashkirova; Arijit Ray; Rupayan Mallick; Sarah Adel Bargal; Jianming Zhang 001; Ranjay Krishna; Kate Saenko (CoRR, 2023)

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

Tell Me What's Next: Textual Foresight for Generic UI Representations. - Andrea Burns; Kate Saenko; Bryan A. Plummer (ACL (Findings), 2024)

Koala: Key Frame-Conditioned Long Video-LLM. - Reuben Tan; Ximeng Sun; Ping Hu 001; Jui-Hsien Wang; Hanieh Deilamsalehy; Bryan A. Plummer; Bryan C. Russell; Kate Saenko (CVPR, 2024)

Concept Arithmetics for Circumventing Concept Inhibition in Diffusion Models. - Vitali Petsiuk; Kate Saenko (ECCV (88), 2024)

From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Spurious Correlations in Image Recognition. - Maan Qraitem; Kate Saenko; Bryan A. Plummer (ECCV (58), 2024)

Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths. - Ximeng Sun; Rameswar Panda; Chun-Fu Richard Chen; Naigang Wang; Bowen Pan; Aude Oliva; Rogério Feris; Kate Saenko (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)

SynCDR : Training Cross Domain Retrieval Models with Synthetic Data. - Samarth Mishra; Kate Saenko; Venkatesh Saligrama (CoRR, 2024)

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

An Introduction to Vision-Language Modeling. - Florian Bordes; Richard Yuanzhe Pang; Anurag Ajay; Alexander C. Li; Adrien Bardes; Suzanne Petryk; Oscar Mañas; Zhiqiu Lin; Anas Mahmoud 002; Bargav Jayaraman; Mark Ibrahim; Melissa Hall; et al. (CoRR, 2024)

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

SAT: Spatial Aptitude Training for Multimodal Language Models. - Arijit Ray; Jiafei Duan; Reuben Tan; Dina Bashkirova; Rose Hendrix; Kiana Ehsani; Aniruddha Kembhavi; Bryan A. Plummer; Ranjay Krishna; Kuo-Hao Zeng; Kate Saenko (CoRR, 2024)

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

Video Frame Interpolation With Many-to-Many Splatting and Spatial Selective Refinement. - Ping Hu 001; Simon Niklaus; Lu Zhang 053; Stan Sclaroff; Kate Saenko (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Guest Editorial: Special Issue on the Promises and Dangers of Large Vision Models. - Kaiyang Zhou; Ziwei Liu 002; Xiaohua Zhai; Chunyuan Li; Kate Saenko (Int. J. Comput. Vis., 2024)

DualCoOp++: Fast and Effective Adaptation to Multi-Label Recognition With Limited Annotations. - Ping Hu 001; Ximeng Sun; Stan Sclaroff; Kate Saenko (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

SPARC: Score Prompting and Adaptive Fusion for Zero-Shot Multi-Label Recognition in Vision-Language Models. - Kevin Miller; Aditya Gangrade; Samarth Mishra; Kate Saenko; Venkatesh Saligrama (CVPR, 2025)

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

KiVA: Kid-inspired Visual Analogies for Testing Large Multimodal Models. - Eunice Yiu; Maan Qraitem; Anisa Noor Majhi; Charlie Wong; Yutong Bai; Shiry Ginosar; Alison Gopnik; 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)

Enhancing Compositional Reasoning in Vision-Language Models with Synthetic Preference Data. - Samarth Mishra; Kate Saenko; Venkatesh Saligrama (CoRR, 2025)