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Damien Teney

  1. Vision-and-Language Navigation: Interpreting visually-grounded\n navigation instructions in real environments
    2017/11/20 by Peter J. Anderson, Qi Wu, Anderson, Peter +15 · 127 citations
    Computer Science · #Multimodal Machine Learning Applications #Speech and dialogue systems #Domain Adaptation and Few-Shot Learning
  2. Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models
    2021/08/09 by Zheyuan Liu, Liu, Zheyuan, Cristian Rodríguez-Opazo +5 · 36 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Multimodal Machine Learning Applications
  3. Neural Redshift: Random Networks are not Random Functions
    2024/03/04 by Damien Teney, Armand Nicolicioiu, Valentin Hartmann +1 · 3 voices · 10 citations
    #cs.LG #cs.AI #cs.CV
  4. Visual Question Answering: A Survey of Methods and Datasets
    2016/07/20 by Qi Wu, Wu, Qi, Damien Teney +9 · 14 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Multimodal Machine Learning Applications
  5. Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
    2021/05/12 by Damien Teney, Ehsan Abbasnejad, Teney, Damien +5 · 7 citations
    Computer Science · #AI in cancer detection #Computer Vision and Pattern Recognition (cs.CV) #Digital Imaging for Blood Diseases #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG)
  6. ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets
    2022/09/01 by Damien Teney, Teney, Damien, Seung‐June Oh +4 · 8 citations
    Computer Science · #Machine Learning and Data Classification #Explainable Artificial Intelligence (XAI) #Data Stream Mining Techniques
  7. Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encoder
    2023/05/25 by Zheyuan Liu, Liu, Zheyuan, Weixuan Sun +5 · 6 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
  8. Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in\n Visual Question Answering
    2021/04/07 by Corentin Dancette, Dancette, Corentin, Rémi Cadène +5 · 4 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Multimodal Machine Learning Applications
  9. SelecMix: Debiased Learning by Contradicting-pair Sampling
    2022/11/04 by Inwoo Hwang, Sang-Jun Lee, Hwang, Inwoo +11 · 5 citations
    Computer Science · Environmental Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Human Pose and Action Recognition #Hydrological Forecasting Using AI #Machine Learning (cs.LG) #Machine Learning and Data Classification
  10. Active Learning by Feature Mixing
    2022/03/14 by Amin Parvaneh, Ehsan Abbasnejad, Parvaneh, Amin +9 · 3 citations
    Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning and Algorithms #Machine Learning and Data Classification #Oil and Gas Production Techniques
  11. V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive\n Matrices
    2019/07/29 by Damien Teney, Teney, Damien, Peng Wang +9 · 2 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image Retrieval and Classification Techniques #Multimodal Machine Learning Applications
  12. Learning What Makes a Difference from Counterfactual Examples and\n Gradient Supervision
    2020/04/19 by Damien Teney, Teney, Damien, Ehsan Abbasnedjad +3 · 2 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Topic Modeling
  13. Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning
    2022/07/06 by Damien Teney, Teney, Damien, Maxime Peyrard +3 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
  14. CulturePark: Boosting Cross-cultural Understanding in Large Language Models
    2024/05/24 by Cheng Li, Li, Cheng, Damien Teney +9 · 3 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Natural Language Processing Techniques
  15. Can You Learn to See Without Images? Procedural Warm-Up for Vision Transformers
    2025/11/17 by Zachary Shinnick, Shinnick, Zachary, Liangze Jiang +7 · 2 voices · 1 citation
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #cs.CV
  16. Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge
    2021/01/15 by Violetta Shevchenko, Damien Teney, Shevchenko, Violetta +5 · 1 citation
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Topic Modeling
  17. Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
    2025/03/13 by Damien Teney, Teney, Damien, Liangze Jiang +5 · 1 voice · 2 citations
    Decision Sciences · Economics, Econometrics and Finance · #Economic Policies and Impacts #Economic Theory and Institutions #Leadership, Behavior, and Decision-Making Studies #cs.CV #cs.LG
  18. Leaner Transformers: More Heads, Less Depth
    2025/05/27 by Hemanth Saratchandran, Damien Teney, Saratchandran, Hemanth +3 · 2 voices · 3 citations
    Engineering · #Manufacturing Process and Optimization #cs.CV #cs.LG
  19. ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning
    2023/10/08 by Lu Wang, Lu, Wang, Hao Yu +15 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Privacy-Preserving Technologies in Data
  20. Transformers Pretrained on Procedural Data Contain Modular Structures for Algorithmic Reasoning
    2025/05/28 by Zachary Shinnick, Liangze Jiang, Shinnick, Zachary +7 · 3 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Topic Modeling
  21. Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks
    2023/10/03 by Luca Scimeca, Scimeca, Luca, Alexander Rubinstein +7 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Music and Audio Processing
  22. Scalable Ensemble Diversification for OOD Generalization and Detection
    2024/09/25 by Alexander Rubinstein, Rubinstein, Alexander, Luca Scimeca +5 · 1 voice · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.AI #cs.CV #cs.LG
  23. Can Transformers Really Do It All? On the Compatibility of Inductive Biases Across Tasks
    2026/07/20 by Damien Teney, Liangze Jiang, Hemanth Saratchandran +1
    #cs.LG