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Flammarion, Nicolas

  1. Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
    2024/04/02 by Maksym Andriushchenko, Andriushchenko, Maksym, Francesco Croce +3 · 4 voices · 85 citations
    Computer Science · Mathematics · #Artificial Intelligence (cs.AI) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.AI #cs.CR #cs.LG #stat.ML
  2. Why Do We Need Weight Decay in Modern Deep Learning?
    2023/10/06 by Francesco D'Angelo, Maksym Andriushchenko, D'Angelo, Francesco +5 · 5 voices · 10 citations
    #cs.LG
  3. Square Attack: a query-efficient black-box adversarial attack via random search
    2019/11/29 by Andriushchenko, Maksym, Croce, Francesco, Flammarion, Nicolas +1 · 52 citations
    #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  4. RobustBench: a standardized adversarial robustness benchmark
    2020/10/19 by Croce, Francesco, Andriushchenko, Maksym, Sehwag, Vikash +5 · 49 citations
    #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  5. JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
    2024/03/28 by Patrick Chao, Edoardo Debenedetti, Chao, Patrick +21 · 91 citations
    Computer Science · #Authorship Attribution and Profiling #Cryptography and Security (cs.CR) #Digital and Cyber Forensics #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques
  6. Towards Understanding Sharpness-Aware Minimization
    2022/06/13 by Maksym Andriushchenko, Nicolas Flammarion, Andriushchenko, Maksym +1 · 19 citations
    Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  7. A Modern Look at the Relationship between Sharpness and Generalization
    2023/02/14 by Maksym Andriushchenko, Andriushchenko, Maksym, Francesco Croce +7 · 16 citations
    Computer Science · Engineering · #FOS: Computer and information sciences #Image Processing Techniques and Applications #Industrial Vision Systems and Defect Detection #Machine Learning (cs.LG) #Optical measurement and interference techniques
  8. Does Refusal Training in LLMs Generalize to the Past Tense?
    2024/07/16 by Maksym Andriushchenko, Nicolas Flammarion, Andriushchenko, Maksym +1 · 21 citations
    Social Sciences · #Artificial Intelligence in Law
  9. Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning
    2024/02/07 by Hao Zhao, Maksym Andriushchenko, Zhao, Hao +5 · 17 citations
    Engineering · #Computation and Language (cs.CL) #Experimental Learning in Engineering #FOS: Computer and information sciences
  10. Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
    2016/02/17 by Dieuleveut, Aymeric, Nicolas Flammarion, Francis Bach +3 · 7 citations
    Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  11. Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity
    2021/06/17 by Scott Pesme, Loucas Pillaud‐Vivien, Pesme, Scott +3 · 6 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and ELM #Markov Chains and Monte Carlo Methods #Neural Networks and Applications #Privacy-Preserving Technologies in Data #Stochastic Gradient Optimization Techniques
  12. Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity
    2019/07/25 by Mou, Wenlong, Flammarion, Nicolas, Wainwright, Martin J. +1 · 5 citations
    #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Probability (math.PR) #Statistics Theory (math.ST)
  13. Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
    2022/06/02 by Étienne Boursier, Loucas Pillaud‐Vivien, Boursier, Etienne +3 · 7 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
  14. Understanding and Improving Fast Adversarial Training
    2020/07/06 by Maksym Andriushchenko, Andriushchenko, Maksym, Nicolas Flammarion +1 · 6 citations
    Computer Science · #Advanced Neural Network Applications #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  15. Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
    2020/06/23 by Croce, Francesco, Andriushchenko, Maksym, Singh, Naman D. +2 · 5 citations
    #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  16. SGD with Large Step Sizes Learns Sparse Features
    2022/10/11 by Andriushchenko, Maksym, Varre, Aditya, Pillaud-Vivien, Loucas +1 · 6 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  17. On the effectiveness of adversarial training against common corruptions
    2021/03/03 by Kireev, Klim, Andriushchenko, Maksym, Flammarion, Nicolas · 4 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  18. Averaging Stochastic Gradient Descent on Riemannian Manifolds
    2018/02/26 by Tripuraneni, Nilesh, Flammarion, Nicolas, Bach, Francis +1 · 3 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  19. Escaping from saddle points on Riemannian manifolds
    2019/06/18 by Sun, Yue, Flammarion, Nicolas, Fazel, Maryam · 3 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  20. Saddle-to-Saddle Dynamics in Diagonal Linear Networks
    2023/04/02 by Scott Pesme, Pesme, Scott, Nicolas Flammarion +1 · 5 citations
    Computer Science · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Markov Chains and Monte Carlo Methods #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
  21. OS-Harm: A Benchmark for Measuring Safety of Computer Use Agents
    2025/06/17 by Kuntz, Thomas, Duzan, Agatha, Zhao, Hao +4 · 14 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Software Engineering (cs.SE)
  22. Last iterate convergence of SGD for Least-Squares in the Interpolation regime
    2021/02/05 by Aditya Varre, Loucas Pillaud‐Vivien, Varre, Aditya +3 · 3 citations
    Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
  23. From Averaging to Acceleration, There is Only a Step-size
    2015/04/07 by Flammarion, Nicolas, Bach, Francis · 2 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  24. Chain-of-Frames: Advancing Video Understanding in Multimodal LLMs via Frame-Aware Reasoning
    2025/05/31 by Sara Ghazanfari, Francesco Croce, Ghazanfari, Sara +9 · 10 citations
    Computer Science · #Multimodal Machine Learning Applications #Video Analysis and Summarization #Natural Language Processing Techniques
  25. An Efficient Sampling Algorithm for Non-smooth Composite Potentials
    2019/10/01 by Wenlong Mou, Mou, Wenlong, Nicolas Flammarion +5 · 3 citations
    Engineering · Mathematics · #Computation (stat.CO) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference
  26. Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
    2024/04/22 by Javier Rando, Rando, Javier, Francesco Croce +11 · 4 citations
    Computer Science · Economics, Econometrics and Finance · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Law, AI, and Intellectual Property #Law, Economics, and Judicial Systems #Machine Learning (cs.LG)
  27. A Continuized View on Nesterov Acceleration for Stochastic Gradient Descent and Randomized Gossip
    2021/06/10 by Even, Mathieu, Berthier, Raphaël, Bach, Francis +5 · 2 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multiagent Systems (cs.MA) #Optimization and Control (math.OC) #Probability (math.PR)
  28. Optimal Rates of Statistical Seriation
    2016/07/08 by Nicolas Flammarion, Flammarion, Nicolas, Cheng Mao +3 · 3 citations
    Agricultural and Biological Sciences · Computer Science · Mathematics · #62G08 #Advanced Statistical Methods and Models #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #FOS: Mathematics #Face and Expression Recognition #Machine Learning (stat.ML) #Sensory Analysis and Statistical Methods #Statistics Theory (math.ST)
  29. Label noise (stochastic) gradient descent implicitly solves the Lasso for quadratic parametrisation
    2022/06/20 by Pillaud-Vivien, Loucas, Reygner, Julien, Flammarion, Nicolas · 2 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  30. Penalising the biases in norm regularisation enforces sparsity
    2023/03/02 by Boursier, Etienne, Flammarion, Nicolas · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  31. (S)GD over Diagonal Linear Networks: Implicit Regularisation, Large Stepsizes and Edge of Stability
    2023/02/17 by Even, Mathieu, Pesme, Scott, Gunasekar, Suriya +1 · 2 citations
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  32. Sharpness-Aware Minimization Leads to Low-Rank Features
    2023/05/25 by Andriushchenko, Maksym, Bahri, Dara, Mobahi, Hossein +1 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  33. Fast Mean Estimation with Sub-Gaussian Rates
    2019/02/06 by Yeshwanth Cherapanamjeri, Nicolas Flammarion, Cherapanamjeri, Yeshwanth +3 · 1 citation
    Computer Science · Mathematics · #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Markov Chains and Monte Carlo Methods #Statistics Theory (math.ST)
  34. Online Robust Regression via SGD on the l1 loss
    2020/07/01 by Scott Pesme, Pesme, Scott, Nicolas Flammarion +1 · 1 citation
    Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
  35. Optimal Robust Linear Regression in Nearly Linear Time
    2020/07/16 by Cherapanamjeri, Yeshwanth, Aras, Efe, Tripuraneni, Nilesh +3 · 1 citation
    #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  36. Linear Speedup in Personalized Collaborative Learning
    2021/11/10 by Chayti, El Mahdi, Karimireddy, Sai Praneeth, Stich, Sebastian U. +2 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  37. Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
    2023/06/06 by Kireev, Klim, Andriushchenko, Maksym, Troncoso, Carmela +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
  38. Learning Algorithms in the Limit
    2025/06/18 by Papazov, Hristo, Flammarion, Nicolas · 3 citations
    #Artificial Intelligence (cs.AI) #Data Structures and Algorithms (cs.DS) #FOS: Computer and information sciences #Formal Languages and Automata Theory (cs.FL) #Machine Learning (cs.LG)
  39. Early alignment in two-layer networks training is a two-edged sword
    2024/01/19 by Étienne Boursier, Nicolas Flammarion, Boursier, Etienne +1 · 1 citation
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
  40. Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks
    2024/03/08 by Hristo Papazov, Papazov, Hristo, Scott Pesme +3 · 1 citation
    Computer Science · #Neural Networks and Applications
  41. Implicit Bias of Mirror Flow on Separable Data
    2024/06/18 by Pesme, Scott, Dragomir, Radu-Alexandru, Flammarion, Nicolas · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  42. Is In-Context Learning Sufficient for Instruction Following in LLMs?
    2024/05/30 by Zhao, Hao, Andriushchenko, Maksym, Croce, Francesco +1 · 1 citation
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  43. Learning In-context \pmbn-grams with Transformers: Sub-\pmbn-grams Are Near-stationary Points
    2025/08/18 by Aditya Varre, Gizem Yüce, Varre, Aditya +3 · 2 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling