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Behnam Neyshabur

  1. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
    2024/03/08 by Gemini Robotics Team, Petko Georgiev, Gemini Team +2277 · 4 voices · 763 citations
    Computer Science · #Semantic Web and Ontologies
  2. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
    2025/07/07 by Gheorghe Comanici, Comanici, Gheorghe, Eric Bieber +6844 · 8 voices · 1398 citations
    #cs.CL #cs.AI
  3. Solving Quantitative Reasoning Problems with Language Models
    2022/06/29 by Aitor Lewkowycz, Lewkowycz, Aitor, Anders Andreassen +25 · 1 voice · 359 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.AI #cs.CL #cs.LG
  4. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
    2022/06/09 by Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448 · 3 voices · 185 citations
    #cs.CL #cs.AI #cs.CY #cs.LG #stat.ML
  5. Gemma 2: Improving Open Language Models at a Practical Size
    2024/07/31 by Gemma Team, Morgane Rivière, Shreya Pathak +292 · 435 citations
    Computer Science · #Natural Language Processing Techniques
  6. Sharpness-Aware Minimization for Efficiently Improving Generalization
    2020/10/03 by Pierre Foret, Foret, Pierre, Ariel Kleiner +5 · 182 citations
    Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
  7. Exploring Generalization in Deep Learning
    2017/06/27 by Behnam Neyshabur, Srinadh Bhojanapalli, Neyshabur, Behnam +5 · 55 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Neural Networks and Applications #Anomaly Detection Techniques and Applications
  8. Gemini: A Family of Highly Capable Multimodal Models
    2023/12/19 by Gemini Robotics Team, Rohan Anil, Gemini Team +2692 · 9 voices · 7 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Multimodal Machine Learning Applications #Natural Language Processing Techniques #cs.AI #cs.CL #cs.CV
  9. Norm-Based Capacity Control in Neural Networks
    2015/02/27 by Behnam Neyshabur, Ryota Tomioka, Neyshabur, Behnam +3 · 35 citations
    Computer Science · Engineering · #Advanced Memory and Neural Computing #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE)
  10. Stronger generalization bounds for deep nets via a compression approach
    2018/02/14 by Sanjeev Arora, Rong Ge, Arora, Sanjeev +5 · 45 citations
    Computer Science · #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques
  11. Fantastic Generalization Measures and Where to Find Them
    2019/12/04 by Yiding Jiang, Behnam Neyshabur, Jiang, Yiding +7 · 36 citations
    Computer Science · #Computability, Logic, AI Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and Data Classification
  12. In Search of the Real Inductive Bias: On the Role of Implicit\n Regularization in Deep Learning
    2014/12/20 by Behnam Neyshabur, Ryota Tomioka, Neyshabur, Behnam +3 · 28 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications
  13. A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks
    2017/07/29 by Behnam Neyshabur, Neyshabur, Behnam, Srinadh Bhojanapalli +3 · 25 citations
    Computer Science · Engineering · #Advanced Neural Network Applications #FOS: Computer and information sciences #Fault Detection and Control Systems #Machine Learning (cs.LG) #Neural Networks and Applications
  14. Teaching Algorithmic Reasoning via In-context Learning
    2022/11/15 by Hattie Zhou, Zhou, Hattie, Azade Nova +9 · 2 voices · 11 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling #cs.AI #cs.CL #cs.LG
  15. Long Range Language Modeling via Gated State Spaces
    2022/06/27 by Harsh Mehta, Mehta, Harsh, Ankit Gupta +5 · 33 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Neural Networks and Applications #Topic Modeling
  16. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models
    2023/12/11 by Avi Singh, John D. Co-Reyes, Singh, Avi +76 · 44 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Natural Language Processing Techniques #Topic Modeling
  17. The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks
    2021/10/12 by Rahim Entezari, Hanie Sedghi, Entezari, Rahim +5 · 27 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Stochastic Gradient Optimization Techniques
  18. Exploring Length Generalization in Large Language Models
    2022/07/11 by Cem Anil, Anil, Cem, Yuhuai Wu +17 · 29 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
  19. Global Optimality of Local Search for Low Rank Matrix Recovery
    2016/05/23 by Srinadh Bhojanapalli, Bhojanapalli, Srinadh, Behnam Neyshabur +3 · 13 citations
    Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Microwave Imaging and Scattering Analysis #Numerical methods in inverse problems #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
  20. Path-SGD: Path-Normalized Optimization in Deep Neural Networks
    2015/06/08 by Behnam Neyshabur, Neyshabur, Behnam, Ruslan Salakhutdinov +3 · 12 citations
    Computer Science · Engineering · #Advanced Neural Network Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural and Evolutionary Computing (cs.NE) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  21. Deep Learning Through the Lens of Example Difficulty
    2021/06/17 by Robert John Nicholas Baldock, Baldock, Robert J. N., Hartmut Maennel +3 · 13 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  22. Block-Recurrent Transformers
    2022/03/11 by DeLesley Hutchins, Imanol Schlag, Hutchins, DeLesley +7 · 11 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Bioinformatics #Natural Language Processing Techniques #Neural and Evolutionary Computing (cs.NE) #Topic Modeling
  23. Geometry of Optimization and Implicit Regularization in Deep Learning
    2017/05/08 by Behnam Neyshabur, Neyshabur, Behnam, Ryota Tomioka +5 · 13 citations
    Computer Science · Engineering · #Advanced Numerical Analysis Techniques #FOS: Computer and information sciences #Image and Object Detection Techniques #Machine Learning (cs.LG) #Medical Image Segmentation Techniques
  24. REPAIR: REnormalizing Permuted Activations for Interpolation Repair
    2022/11/15 by Keller Jordan, Hanie Sedghi, Jordan, Keller +7 · 12 citations
    Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  25. Understanding the Failure Modes of Out-of-Distribution Generalization
    2020/10/29 by Vaishnavh Nagarajan, Anders Andreassen, Nagarajan, Vaishnavh +3 · 9 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  26. When Do Curricula Work?
    2020/12/05 by Xiaoxia Wu, Ethan Dyer, Wu, Xiaoxia +3 · 10 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Topic Modeling #electronic engineering #information engineering
  27. Corralling a Band of Bandit Algorithms
    2016/12/19 by Alekh Agarwal, Agarwal, Alekh, Haipeng Luo +5 · 7 citations
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
  28. Data Scaling Laws in NMT: The Effect of Noise and Architecture
    2022/02/04 by Yamini Bansal, Bansal, Yamini, Behrooz Ghorbani +13 · 8 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #Machine Learning and Data Classification
  29. On Symmetric and Asymmetric LSHs for Inner Product Search
    2014/10/21 by Behnam Neyshabur, Neyshabur, Behnam, Nathan Srebro +1 · 5 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Algorithms and Data Compression #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Metaheuristic Optimization Algorithms Research
  30. Stabilizing GAN Training with Multiple Random Projections
    2017/05/22 by Behnam Neyshabur, Srinadh Bhojanapalli, Neyshabur, Behnam +3 · 4 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Image Processing and 3D Reconstruction #Machine Learning (cs.LG) #Neural Networks and Applications
  31. Data-Dependent Path Normalization in Neural Networks
    2015/11/20 by Behnam Neyshabur, Ryota Tomioka, Neyshabur, Behnam +5 · 2 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
  32. Path-Normalized Optimization of Recurrent Neural Networks with ReLU\n Activations
    2016/05/23 by Behnam Neyshabur, Neyshabur, Behnam, Yuhuai Wu +5 · 2 citations
    Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Natural Language Processing Techniques #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #Topic Modeling
  33. Towards Learning Convolutions from Scratch
    2020/07/27 by Behnam Neyshabur, Neyshabur, Behnam · 1 citation
    Computer Science · #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) #Machine Learning (stat.ML) #Machine Learning and Data Classification
  34. Are wider nets better given the same number of parameters?
    2020/10/27 by Anna Golubeva, Golubeva, Anna, Behnam Neyshabur +3 · 1 citation
    Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM
  35. Convexifying Transformers: Improving optimization and understanding of transformer networks
    2022/11/20 by Tolga Ergen, Behnam Neyshabur, Ergen, Tolga +3 · 1 citation
    Computer Science · Engineering · #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  36. NeurIPS 2020 Competition: Predicting Generalization in Deep Learning
    2020/12/14 by Yiding Jiang, Pierre Foret, Jiang, Yiding +17 · 2 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)