vix.ing · top · new · best · stats · spec

Goldblum, Micah

  1. A Cookbook of Self-Supervised Learning
    2023/04/24 by Randall Balestriero, Mark Ibrahim, Balestriero, Randall +36 · 2 voices · 32 citations
    Computer Science · #Machine Learning and Data Classification
  2. Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models
    2022/12/07 by Gowthami Somepalli, Somepalli, Gowthami, Vasu Singla +7 · 7 voices · 58 citations
    Computer Science · Neuroscience · #Generative Adversarial Networks and Image Synthesis #Digital Media Forensic Detection #Aesthetic Perception and Analysis
  3. Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
    2024/01/22 by Abhimanyu Hans, Avi Schwarzschild, Hans, Abhimanyu +13 · 2 voices · 60 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #Text Readability and Simplification
  4. Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
    2022/08/19 by Arpit Bansal, Bansal, Arpit, Eitan Borgnia +16 · 6 voices · 22 citations
    Computer Science · #Generative Adversarial Networks and Image Synthesis
  5. Understanding and Mitigating Copying in Diffusion Models
    2023/05/31 by Gowthami Somepalli, Somepalli, Gowthami, Vasu Singla +7 · 3 voices · 30 citations
    Computer Science · #Generative Adversarial Networks and Image Synthesis #cs.CR #cs.CV #cs.LG
  6. Baseline Defenses for Adversarial Attacks Against Aligned Language Models
    2023/09/01 by Neel Jain, Jain, Neel, Avi Schwarzschild +17 · 100 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Topic Modeling #Natural Language Processing Techniques
  7. AI Benchmark Half-Life in Recursive Corpora: A Theory of Validity Decay under Semantic Leakage and Regeneration
    2024/06/27 by White, Colin, Samuel Dooley, Manley Roberts +29 · 101 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Digital Rights Management and Security #FOS: Computer and information sciences #Machine Learning (cs.LG)
  8. The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
    2023/04/11 by Micah Goldblum, Marc Finzi, Goldblum, Micah +5 · 2 voices · 9 citations
    Computer Science · #Computability, Logic, AI Algorithms #Machine Learning and Algorithms #Machine Learning and Data Classification #cs.LG #stat.ML
  9. Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery
    2023/02/07 by Yuxin Wen, Neel Jain, Wen, Yuxin +9 · 1 voice · 38 citations
    Biochemistry, Genetics and Molecular Biology · Computer Science · #Computational Physics and Python Applications #Gene expression and cancer classification #cs.CL #cs.LG
  10. Universal Guidance for Diffusion Models
    2023/02/14 by Arpit Bansal, Hongmin Chu, Bansal, Arpit +11 · 50 citations
    Computer Science · Medicine · #Generative Adversarial Networks and Image Synthesis #Advanced Mathematical Modeling in Engineering #Advanced Neuroimaging Techniques and Applications
  11. The Intrinsic Dimension of Images and Its Impact on Learning
    2021/04/18 by Phillip B. Pope, Pope, Phillip, Chen Zhu +7 · 36 citations
    Computer Science · Engineering · Medicine · #Adversarial Robustness in Machine Learning #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #I.2.6 #I.5.1 #Image Processing Techniques and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  12. SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
    2021/06/02 by Somepalli, Gowthami, Goldblum, Micah, Schwarzschild, Avi +2 · 31 citations
    #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  13. When Do Neural Nets Outperform Boosted Trees on Tabular Data?
    2023/05/04 by Duncan C. McElfresh, Sujay Khandagale, McElfresh, Duncan +13 · 34 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning #Imbalanced Data Classification Techniques
  14. On the Reliability of Watermarks for Large Language Models
    2023/06/07 by Kirchenbauer, John, Geiping, Jonas, Wen, Yuxin +7 · 29 citations
    #Computation and Language (cs.CL) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  15. Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses
    2020/12/18 by Micah Goldblum, Goldblum, Micah, Dimitris Tsipras +15 · 13 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Network Security and Intrusion Detection #Advanced Malware Detection Techniques
  16. Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch
    2021/06/16 by Hossein Souri, Souri, Hossein, Liam Fowl +7 · 13 citations
    Computer Science · Medicine · #Adversarial Robustness in Machine Learning #Artificial Intelligence in Healthcare and Education #Autopsy Techniques and Outcomes #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  17. Measuring Style Similarity in Diffusion Models
    2024/04/01 by Gowthami Somepalli, Somepalli, Gowthami, Anubhav Gupta +13 · 22 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Music and Audio Processing
  18. Large Language Models Must Be Taught to Know What They Don't Know
    2024/06/12 by Kapoor, Sanyam, Gruver, Nate, Roberts, Manley +7 · 20 citations
    #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  19. Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
    2020/06/22 by Avi Schwarzschild, Micah Goldblum, Schwarzschild, Avi +7 · 13 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications
  20. An Open Review of OpenReview: A Critical Analysis of the Machine Learning Conference Review Process
    2020/10/11 by David Tran, Alexander V Valtchanov, Tran, David +11 · 8 citations
    Computer Science · Decision Sciences · Social Sciences · #Computational and Text Analysis Methods #Computers and Society (cs.CY) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #scientometrics and bibliometrics research
  21. Adversarial Examples Make Strong Poisons
    2021/06/21 by Liam Fowl, Fowl, Liam, Micah Goldblum +9 · 8 citations
    Computer Science · Pharmacology, Toxicology and Pharmaceutics · Social Sciences · #Adversarial Robustness in Machine Learning #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Forensic Fingerprint Detection Methods #Forensic Toxicology and Drug Analysis #Machine Learning (cs.LG)
  22. Non-Vacuous Generalization Bounds for Large Language Models
    2023/12/28 by Sanae Lotfi, Lotfi, Sanae, Marc Finzi +9 · 2 voices · 8 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Speech Recognition and Synthesis #Topic Modeling
  23. NEFTune: Noisy Embeddings Improve Instruction Finetuning
    2023/10/09 by Neel Jain, Ping-yeh Chiang, Jain, Neel +23 · 11 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling #Text Readability and Simplification
  24. Where do Models go Wrong? Parameter-Space Saliency Maps for\n Explainability
    2021/08/03 by R. V. Levin, Roman Levin, Manli Shu +10 · 1 voice · 1 citation
    Computer Science · #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning #Machine Learning in Healthcare
  25. Bayesian Model Selection, the Marginal Likelihood, and Generalization
    2022/02/23 by Lotfi, Sanae, Izmailov, Pavel, Benton, Gregory +2 · 8 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  26. Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification
    2022/02/01 by Wen, Yuxin, Geiping, Jonas, Fowl, Liam +2 · 7 citations
    #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  27. LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition
    2021/01/20 by Cherepanova, Valeriia, Goldblum, Micah, Foley, Harrison +4 · 6 citations
    #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  28. PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
    2022/11/24 by Sanae Lotfi, Lotfi, Sanae, Marc Finzi +9 · 8 citations
    Computer Science · Physics and Astronomy · #Advanced Neural Network Applications #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks
  29. Autoregressive Perturbations for Data Poisoning
    2022/06/08 by Pedro Sandoval-Segura, Vasu Singla, Sandoval-Segura, Pedro +9 · 6 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Network Security and Intrusion Detection
  30. The Lie Derivative for Measuring Learned Equivariance
    2022/10/06 by Nate Gruver, Gruver, Nate, Marc Finzi +5 · 6 citations
    Computer Science · Materials Science · Physics and Astronomy · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Model Reduction and Neural Networks #Neural Networks and Applications
  31. Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models
    2021/10/25 by Liam Fowl, Jonas Geiping, Fowl, Liam +7 · 5 citations
    Computer Science · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Privacy-Preserving Technologies in Data
  32. TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
    2024/02/17 by Benjamin Feuer, Feuer, Benjamin, Robin Tibor Schirrmeister +13 · 8 citations
    Computer Science · #Embedded Systems Design Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Service-Oriented Architecture and Web Services #Software-Defined Networks and 5G
  33. Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
    2023/10/30 by Micah Goldblum, Hossein Souri, Goldblum, Micah +23 · 7 citations
    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) #Multimodal Machine Learning Applications
  34. Small Batch Size Training for Language Models: When Vanilla SGD Works, and Why Gradient Accumulation Is Wasteful
    2025/07/09 by Martin Marek, Marek, Martin, Sanae Lotfi +7 · 4 voices · 12 citations
    Computer Science · Medicine · #Topic Modeling #Natural Language Processing Techniques #Artificial Intelligence in Healthcare and Education
  35. Understanding Generalization through Visualizations
    2019/06/07 by Wei Huang, Zeyad Emam, Huang, W. Ronny +11 · 4 citations
    Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Neural and Evolutionary Computing (cs.NE) #Stochastic Gradient Optimization Techniques
  36. Towards Transferable Adversarial Attacks on Vision Transformers
    2021/09/09 by Wei, Zhipeng, Chen, Jingjing, Goldblum, Micah +3 · 4 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  37. Commercial LLM Agents Are Already Vulnerable to Simple Yet Dangerous Attacks
    2025/02/12 by Ang Li, Li, Ang, Yin Zhou +7 · 12 citations
    Computer Science · #Security and Verification in Computing #Web Application Security Vulnerabilities #Information and Cyber Security
  38. Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
    2021/06/08 by Avi Schwarzschild, Eitan Borgnia, Schwarzschild, Avi +11 · 4 citations
    Computer Science · #Advanced Neural Network Applications #Machine Learning and Data Classification #Explainable Artificial Intelligence (XAI)
  39. Zebra-CoT: A Dataset for Interleaved Vision Language Reasoning
    2025/07/22 by Ang Li, Li, Ang, Charles Wang +21 · 1 voice · 14 citations
    Computer Science · #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.CL #cs.CV #cs.LG
  40. Encoding Robustness to Image Style via Adversarial Feature Perturbations
    2020/09/18 by Manli Shu, Zuxuan Wu, Shu, Manli +5 · 3 citations
    Computer Science · #Advanced Image Processing Techniques #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG)
  41. Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
    2022/10/19 by Wen, Yuxin, Bansal, Arpit, Kazemi, Hamid +4 · 4 citations
    #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  42. Style Outweighs Substance: Failure Modes of LLM Judges in Alignment Benchmarking
    2024/09/23 by Benjamin Feuer, Micah Goldblum, Feuer, Benjamin +13 · 7 citations
    Economics, Econometrics and Finance · Social Sciences · #Law, Economics, and Judicial Systems #European and International Contract Law #Legal Systems and Judicial Processes
  43. Stochastic Training is Not Necessary for Generalization
    2021/09/29 by Jonas Geiping, Micah Goldblum, Geiping, Jonas +7 · 3 citations
    Computer Science · #Advanced Neural Network Applications #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
  44. Compute Better Spent: Replacing Dense Layers with Structured Matrices
    2024/06/10 by Shikai Qiu, Qiu, Shikai, Andres Potapczynski +7 · 1 voice · 4 citations
    #cs.LG
  45. Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition
    2022/10/18 by Dooley, Samuel, Sukthanker, Rhea Sanjay, Dickerson, John P. +3 · 3 citations
    #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  46. How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization
    2022/10/12 by Jonas Geiping, Geiping, Jonas, Micah Goldblum +9 · 3 citations
    Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and Data Classification
  47. What do Vision Transformers Learn? A Visual Exploration
    2022/12/13 by Ghiasi, Amin, Kazemi, Hamid, Borgnia, Eitan +5 · 3 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
  48. Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks
    2020/02/17 by Goldblum, Micah, Reich, Steven, Fowl, Liam +3 · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  49. Gemstones: A Model Suite for Multi-Faceted Scaling Laws
    2025/02/07 by Sean McLeish, McLeish, Sean, John Kirchenbauer +12 · 6 citations
    Earth and Planetary Sciences · #Mineralogy and Gemology Studies #Geology and Paleoclimatology Research #Paleontology and Stratigraphy of Fossils
  50. Refusal Tokens: A Simple Way to Calibrate Refusals in Large Language Models
    2024/12/09 by Neel Jain, Jain, Neel, Aditya Shrivastava +15 · 1 voice · 4 citations
    #cs.LG #cs.CL
  51. Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective
    2022/03/15 by Gowthami Somepalli, Liam Fowl, Somepalli, Gowthami +13 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Stochastic Gradient Optimization Techniques #Neural Networks and Applications
  52. Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations
    2022/01/31 by Amin Ghiasi, Ghiasi, Amin, Hamid Kazemi +9 · 2 citations
    Computer Science · Earth and Planetary Sciences · #Domain Adaptation and Few-Shot Learning #Advanced Neural Network Applications #Seismic Imaging and Inversion Techniques
  53. Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release
    2021/02/16 by Liam Fowl, Ping-yeh Chiang, Fowl, Liam +11 · 2 citations
    Computer Science · #Advanced Malware Detection Techniques #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Network Security and Intrusion Detection
  54. Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models
    2022/01/29 by Fowl, Liam, Geiping, Jonas, Reich, Steven +4 · 2 citations
    #Computation and Language (cs.CL) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  55. Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors
    2022/05/20 by Ravid Shwartz-Ziv, Shwartz-Ziv, Ravid, Micah Goldblum +11 · 2 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Gaussian Processes and Bayesian Inference #Adversarial Robustness in Machine Learning
  56. Poisons that are learned faster are more effective
    2022/04/19 by Pedro Sandoval-Segura, Sandoval-Segura, Pedro, Vasu Singla +11 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Privacy-Preserving Technologies in Data
  57. K-SAM: Sharpness-Aware Minimization at the Speed of SGD
    2022/10/23 by Ni, Renkun, Chiang, Ping-yeh, Geiping, Jonas +3 · 2 citations
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  58. Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers
    2022/11/28 by Wanqian Yang, Yang, Wanqian, Polina Kirichenko +5 · 2 citations
    Computer Science · #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Music and Audio Processing #Topic Modeling
  59. Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness
    2023/02/06 by Yuancheng Xu, Yanchao Sun, Xu, Yuancheng +7 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Anomaly Detection Techniques and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG)
  60. Searching for Efficient Linear Layers over a Continuous Space of Structured Matrices
    2024/10/03 by Potapczynski, Andres, Qiu, Shikai, Finzi, Marc +6 · 3 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  61. Adaptive Retention & Correction: Test-Time Training for Continual Learning
    2024/05/23 by Hao Chen, Chen, Haoran, Micah Goldblum +5 · 3 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)
  62. DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations
    2021/03/02 by Eitan Borgnia, Jonas Geiping, Borgnia, Eitan +15 · 2 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Data Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Privacy-Preserving Technologies in Data
  63. Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory
    2019/10/01 by Goldblum, Micah, Geiping, Jonas, Schwarzschild, Avi +2 · 1 citation
    #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC)
  64. WITCHcraft: Efficient PGD attacks with random step size
    2019/11/18 by Chiang, Ping-Yeh, Geiping, Jonas, Goldblum, Micah +4 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Signal Processing (eess.SP) #electronic engineering #information engineering
  65. Data Augmentation for Meta-Learning
    2020/10/14 by Ni, Renkun, Goldblum, Micah, Sharaf, Amr +2 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  66. The Uncanny Similarity of Recurrence and Depth
    2021/02/22 by Avi Schwarzschild, Schwarzschild, Avi, Arjun Gupta +7 · 1 citation
    Computer Science · #Advanced Neural Network Applications #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Neural Networks and Applications
  67. Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models
    2024/07/25 by Sanae Lotfi, Lotfi, Sanae, Yilun Kuang +9 · 1 voice · 3 citations
    #stat.ML #cs.LG
  68. What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning
    2021/02/26 by Geiping, Jonas, Fowl, Liam, Somepalli, Gowthami +3 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  69. Technical Challenges for Training Fair Neural Networks
    2021/02/12 by Cherepanova, Valeriia, Nanda, Vedant, Goldblum, Micah +2 · 1 citation
    #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  70. Perspectives on the State and Future of Deep Learning - 2023
    2023/12/07 by Micah Goldblum, Anima Anandkumar, Goldblum, Micah +17 · 3 voices
    #cs.AI #cs.LG
  71. Comparing Human and Machine Bias in Face Recognition
    2021/10/15 by Samuel Dooley, Dooley, Samuel, Ryan Downing +25 · 1 voice
    Computer Science · Neuroscience · #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Face Recognition and Perception #Face and Expression Recognition #Face recognition and analysis #Machine Learning (cs.LG) #cs.AI #cs.CV #cs.CY #cs.LG
  72. A Deep Dive into Dataset Imbalance and Bias in Face Identification
    2022/03/15 by Cherepanova, Valeriia, Reich, Steven, Dooley, Samuel +3 · 1 citation
    #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  73. Simplifying Neural Network Training Under Class Imbalance
    2023/12/05 by Ravid Shwartz-Ziv, Shwartz-Ziv, Ravid, Micah Goldblum +7 · 1 voice · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.AI #cs.LG
  74. What Can We Learn from Unlearnable Datasets?
    2023/05/30 by Sandoval-Segura, Pedro, Singla, Vasu, Geiping, Jonas +2 · 1 citation
    #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  75. Bring Your Own Data! Self-Supervised Evaluation for Large Language Models
    2023/06/23 by Jain, Neel, Saifullah, Khalid, Wen, Yuxin +6 · 1 citation
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG)
  76. Transformers Boost the Performance of Decision Trees on Tabular Data across Sample Sizes
    2025/02/04 by Jayawardhana, Mayuka, Renbo, Dooley, Samuel +6 · 2 citations
    #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2.6 #I.2.7 #I.2.m #Machine Learning (cs.LG)
  77. Teaching Pretrained Language Models to Think Deeper with Retrofitted Recurrence
    2025/11/10 by McLeish, Sean, Li, Ang, Kirchenbauer, John +7 · 2 citations
    Computer Science · #Topic Modeling #Multimodal Machine Learning Applications #Natural Language Processing Techniques
  78. vTune: Verifiable Fine-Tuning for LLMs Through Backdooring
    2024/11/10 by Arka Pal, Zhang, Eva, Pal, Arka +4 · 1 citation
    Computer Science · Decision Sciences · Engineering · #Artificial Intelligence (cs.AI) #Computers and Society (cs.CY) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Real-time simulation and control systems #Simulation Techniques and Applications #VLSI and Analog Circuit Testing
  79. Far from the Shallow: Brain-Predictive Reasoning Embedding through Residual Disentanglement
    2025/10/26 by He, Linyang, Zhong, Tianjun, Antonello, Richard +3 · 1 voice · 1 citation
    #Computation and Language (cs.CL) #FOS: Biological sciences #FOS: Computer and information sciences #Neurons and Cognition (q-bio.NC)
  80. Closing the Train-Test Gap in World Models for Gradient-Based Planning
    2025/12/10 by Parthasarathy, Arjun, Kalra, Nimit, Agrawal, Rohun +4 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG) #Robotics (cs.RO)