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Nicolas Flammarion

  1. Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
    2024/04/02 by Maksym Andriushchenko, Andriushchenko, Maksym, Francesco Croce +3 · 4 voices · 86 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, D'Angelo, Francesco, Maksym Andriushchenko +5 · 5 voices · 10 citations
    #cs.LG
  3. JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
    2024/03/28 by Patrick Chao, Edoardo Debenedetti, Chao, Patrick +21 · 92 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
  4. Towards Understanding Sharpness-Aware Minimization
    2022/06/13 by Maksym Andriushchenko, Andriushchenko, Maksym, Nicolas Flammarion +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
  5. 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
  6. 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
  7. Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning
    2024/02/07 by Hao Zhao, Zhao, Hao, Maksym Andriushchenko +5 · 17 citations
    Engineering · #Computation and Language (cs.CL) #Experimental Learning in Engineering #FOS: Computer and information sciences
  8. Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression
    2016/02/17 by Dieuleveut, Aymeric, Nicolas Flammarion, Flammarion, Nicolas +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
  9. HalluHard: A Hard Multi-Turn Hallucination Benchmark
    2026/02/01 by Dongyang Fan, Sebastien Delsad, Nicolas Flammarion +1 · 9 voices
    #cs.AI #cs.CL
  10. Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity
    2021/06/17 by Scott Pesme, Pesme, Scott, Loucas Pillaud‐Vivien +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
  11. Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs
    2022/06/02 by Étienne Boursier, Boursier, Etienne, Loucas Pillaud‐Vivien +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
  12. 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)
  13. 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
  14. Last iterate convergence of SGD for Least-Squares in the Interpolation regime
    2021/02/05 by Aditya Varre, Varre, Aditya, Loucas Pillaud‐Vivien +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
  15. Chain-of-Frames: Advancing Video Understanding in Multimodal LLMs via Frame-Aware Reasoning
    2025/05/31 by Sara Ghazanfari, Ghazanfari, Sara, Francesco Croce +9 · 10 citations
    Computer Science · #Multimodal Machine Learning Applications #Video Analysis and Summarization #Natural Language Processing Techniques
  16. An Efficient Sampling Algorithm for Non-smooth Composite Potentials
    2019/10/01 by Wenlong Mou, Nicolas Flammarion, Mou, Wenlong +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
  17. Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
    2024/04/22 by Javier Rando, Francesco Croce, Rando, Javier +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)
  18. 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)
  19. Fast Mean Estimation with Sub-Gaussian Rates
    2019/02/06 by Yeshwanth Cherapanamjeri, Cherapanamjeri, Yeshwanth, Nicolas Flammarion +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)
  20. 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
  21. Early alignment in two-layer networks training is a two-edged sword
    2024/01/19 by Étienne Boursier, Boursier, Etienne, Nicolas Flammarion +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
  22. Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks
    2024/03/08 by Hristo Papazov, Scott Pesme, Papazov, Hristo +3 · 1 citation
    Computer Science · #Neural Networks and Applications
  23. Learning In-context \pmbn-grams with Transformers: Sub-\pmbn-grams Are Near-stationary Points
    2025/08/18 by Aditya Varre, Varre, Aditya, Gizem Yüce +3 · 2 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling