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Yann Dauphin

  1. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
    2025/07/07 by Gheorghe Comanici, Eric Bieber, Comanici, Gheorghe +6844 · 8 voices · 1385 citations
    #cs.CL #cs.AI
  2. Hierarchical Neural Story Generation
    2018/05/13 by Angela Fan, Fan, Angela, Mike Lewis +3 · 1 voice · 132 citations
    Computer Science · #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Topic Modeling #cs.CL
  3. mixup: Beyond Empirical Risk Minimization
    2017/10/25 by Hongyi Zhang, Zhang, Hongyi, Moustapha Cissé +5 · 412 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  4. Empirical Analysis of the Hessian of Over-Parametrized Neural Networks
    2017/06/14 by Levent Sagun, Utku Evci, Sagun, Levent +7 · 46 citations
    Computer Science · Engineering · Mathematics · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Random Matrices and Applications
  5. Convolutional Sequence to Sequence Learning
    2017/05/08 by Jonas Gehring, Michael Auli, Gehring, Jonas +7 · 33 citations
    Computer Science · #Algorithms and Data Compression #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
  6. Parseval Networks: Improving Robustness to Adversarial Examples
    2017/04/28 by Moustapha Cissé, Piotr Bojanowski, Cisse, Moustapha +7 · 32 citations
    Computer Science · Physics and Astronomy · #Advanced Optical Sensing Technologies #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  7. Pay Less Attention with Lightweight and Dynamic Convolutions
    2019/01/29 by Felix Wu, Wu, Felix, Angela Fan +7 · 49 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Topic Modeling
  8. On the saddle point problem for non-convex optimization
    2014/05/19 by Razvan Pascanu, Yann Dauphin, Pascanu, Razvan +5 · 10 citations
    Computer Science · Engineering · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Gaussian Processes and Bayesian Inference
  9. Tackling Over-pruning in Variational Autoencoders
    2017/06/09 by Serena Yeung, Yeung, Serena, Anitha Kannan +5 · 7 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Music and Audio Processing
  10. Big Neural Networks Waste Capacity
    2013/01/16 by Yann Dauphin, Dauphin, Yann N., Yoshua Bengio +1 · 5 citations
    Computer Science · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Neural Networks and Applications
  11. A density estimation perspective on learning from pairwise human preferences
    2023/11/23 by Vincent Dumoulin, Dumoulin, Vincent, Daniel D. Johnson +7 · 6 citations
    Computer Science · #Speech and dialogue systems #Topic Modeling #Natural Language Processing Techniques
  12. Gradient Flow in Sparse Neural Networks and How Lottery Tickets Win
    2020/10/07 by Utku Evci, Yani Ioannou, Evci, Utku +5 · 3 citations
    Computer Science · #68T07 #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Stochastic Gradient Optimization Techniques
  13. Strategies for Structuring Story Generation
    2019/02/04 by Angela Fan, Mike Lewis, Fan, Angela +3 · 3 citations
    Computer Science · #Artificial Intelligence in Games #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling
  14. SAM operates far from home: eigenvalue regularization as a dynamical phenomenon
    2023/02/17 by Atish Agarwala, Agarwala, Atish, Yann Dauphin +1 · 3 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and ELM #Neural Networks and Applications
  15. Temperature check: theory and practice for training models with softmax-cross-entropy losses
    2020/10/14 by Atish Agarwala, Jeffrey Pennington, Agarwala, Atish +4 · 2 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG)
  16. EmoNets: Multimodal deep learning approaches for emotion recognition in\n video
    2015/03/05 by Samira Ebrahimi Kahou, Kahou, Samira Ebrahimi, Xavier Bouthillier +34 · 2 citations
    Psychology · Computer Science · #Emotion and Mood Recognition #Face recognition and analysis #Human Pose and Action Recognition
  17. Towards Optimal Adapter Placement for Efficient Transfer Learning
    2024/10/21 by Aleksandra Nowak, Nowak, Aleksandra I., Otniel-Bogdan Mercea +9 · 3 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and ELM #Speech Recognition and Synthesis
  18. Zero-Shot Learning for Semantic Utterance Classification
    2013/12/20 by Yann Dauphin, Dauphin, Yann N., Gökhan Tür +5 · 1 citation
    Computer Science · #Computation and Language (cs.CL) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Text and Document Classification Technologies #Topic Modeling
  19. Simple and Effective Noisy Channel Modeling for Neural Machine\n Translation
    2019/08/15 by Kyra Yee, Yee, Kyra, Nathan Ng +5 · 1 citation
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #Text Readability and Simplification
  20. Avoiding spurious sharpness minimization broadens applicability of SAM
    2025/02/04 by Sidak Pal Singh, Hossein Mobahi, Singh, Sidak Pal +5 · 1 voice · 2 citations
    Computer Science · Engineering · Mathematics · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Ultrasonics and Acoustic Wave Propagation #cs.CL #cs.LG #stat.ML
  21. How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?
    2022/11/22 by Charvi Rastogi, Rastogi, Charvi, Ivan Stelmakh +17 · 2 citations
    Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #Databases (cs.DB) #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Software Engineering Research