- VACoT: Rethinking Visual Data Augmentation with VLMs
2025/12/02 by Zhengzhuo Xu, Xu, Zhengzhuo, Chong Sun +9 · 1 citation
Computer Science · #Adversarial system #Artificial Intelligence (cs.AI) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Multimodal Machine Learning Applications #Perception #Reinforcement learning #Robustness (evolution) #Scheme (mathematics) #Training set #Visual perception #Visual reasoning #Visualization
- Student-Centered Distillation Narrows the Agentic Gap Between Small and Large LLMs
2025/09/12 by Yuanjie Lyu, Chengyu Wang, Lyu, Yuanjie +5 · 2 citations
Computer Science · #Compounding #Distillation #Imitation #Language model #Multimodal Machine Learning Applications #Natural Language Processing Techniques #Prefix #Reinforcement learning #Topic Modeling #Training set #cs.AI #cs.CL
- On the Feasibility of Poisoning Text-to-Image AI Models via Adversarial Mislabeling
2025/06/27 by Stanley Wu, Shengyi Wu, Wu, Stanley +10 · 1 voice
Computer Science · #Adversarial Robustness in Machine Learning #Adversarial system #Generative Adversarial Networks and Image Synthesis #Generative grammar #Key (lock) #Multimodal Machine Learning Applications #Pipeline (software) #Training set #Work (physics)
- A Common Pool of Privacy Problems: Legal and Technical Lessons from a Large-Scale Web-Scraped Machine Learning Dataset
2025/06/20 by Rachel Hong, Hong, Rachel, Jevan Hutson +9 · 2 voices · 4 citations
Computer Science · Social Sciences · #Audit #Confidentiality #Data Protection Act 1998 #Empirical research #Ethics and Social Impacts of AI #Information privacy #Personally identifiable information #Privacy policy #Privacy, Security, and Data Protection #Privacy-Preserving Technologies in Data #Training set
- Unsupervised Elicitation of Language Models
2025/06/11 by Jiaxin Wen, Wen, Jiaxin, Zachary Ankner +23 · 15 voices · 4 citations
Computer Science · #Coherence (philosophical gambling strategy) #Human language #Language model #Language understanding #Machine Learning and Data Classification #Maximization #Multimodal Machine Learning Applications #Reinforcement learning #Topic Modeling #Training set #Unsupervised learning
- The ATLAS Virtual Research Assistant
2025/06/11 by H. F. Stevance, Stevance, H. F., K. Smith +14 · 2 voices · 3 citations
Computer Science · Physics and Astronomy · #Atlas (anatomy) #Computational Physics and Python Applications #Decision tree #Facility management #Metric (unit) #Particle Detector Development and Performance #Particle physics theoretical and experimental studies #Sky #Training set #Workload
- OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens
2025/04/09 by Jiacheng Liu, Liu, Jiacheng, Taylor Blanton +61 · 3 voices · 15 citations
Computer Science · Medicine · #Artificial Intelligence in Healthcare and Education #Data modeling #Language identification #Language model #Natural Language Processing Techniques #Natural language #Topic Modeling #Tracing #Training (meteorology) #Training set #Universal Networking Language
- Quality In, Quality Out: Investigating Training Data's Role in AI Code Generation
2025/03/14 by Cristina Improta, Improta, Cristina, Rosalia Tufano +7 · 4 citations
Computer Science · #Advanced Malware Detection Techniques #Code (set theory) #Code generation #FOS: Computer and information sciences #Inference #Python (programming language) #Quality (philosophy) #Software Engineering (cs.SE) #Software Engineering Research #Software Testing and Debugging Techniques #Software quality #Source code #Training set
- On the Limits of LLM Reasoning: Evidence From Contamination, Translation, and Answer Modification in Multiple-Choice Benchmarks
2025/02/18 by Eva Sánchez Salido, Salido, Eva Sánchez, Julio Gonzalo +4 · 4 voices
Business, Management and Accounting · Computer Science · Engineering · Mathematics · Psychology · #Baseline (sea) #Business Process Modeling and Analysis #Computer science #Conflation #Engineering #Inference #Intelligent Tutoring Systems and Adaptive Learning #Management science #Mathematics #Mathematics education #Memorization #Multiple choice #Natural Language Processing Techniques #Psychology #Stability (learning theory) #Statistics #Test (biology) #Topic Modeling #Training set
- Impact of imperfect annotations on CNN training and performance for instance segmentation and classification in digital pathology
2024/05/14 by Laura Gálvez Jiménez, Christine Decaestecker · 1 citation
Computer Science · #AI in cancer detection #Annotation #Artificial intelligence #Artificial neural network #Computer science #Context (archaeology) #Crowdsourcing #Digital Imaging for Blood Diseases #Digital pathology #Image (mathematics) #Machine Learning and Data Classification #Machine learning #Market segmentation #Noise (video) #Overfitting #Pattern recognition (psychology) #Process (computing) #Segmentation #Set (abstract data type) #Task (project management) #Training set
- CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
2024/04/24 by Sachin Mehta, Mehta, Sachin, Maxwell Horton +13 · 1 voice · 3 citations
Computer Science · #Artificial intelligence #Cartography #Computer science #Geography #Handwritten Text Recognition Techniques #Image (mathematics) #Information retrieval #Pattern recognition (psychology) #Scale (ratio) #Training set #World Wide Web
- Improving Text Embeddings with Large Language Models
2023/12/31 by Liang Wang, Wang, Liang, Nan Yang +9 · 4 voices · 106 citations
Computer Science · #Artificial intelligence #Computer science #Embedding #Hate Speech and Cyberbullying Detection #Labeled data #Leverage (statistics) #Natural Language Processing Techniques #Natural language processing #Simple (philosophy) #Synthetic data #Topic Modeling #Training set
- Scalable Data Ablation Approximations for Language Models through Modular Training and Merging
2024/01/01 by Clara Na, Ian Magnusson, Ananya Harsh Jha +4 · 1 voice · 2 citations
Computer Science · Engineering · #Ablation #Aerospace engineering #Artificial intelligence #Computer science #Data modeling #Database #Engineering #Modular design #Natural Language Processing Techniques #Programming language #Scalability #Software engineering #Topic Modeling #Training (meteorology) #Training set
- Scalable Extraction of Training Data from (Production) Language Models
2023/11/28 by Milad Nasr, Nicholas Carlini, Nasr, Milad +17 · 21 voices · 112 citations
Computer Science · #Adversarial Robustness in Machine Learning #Adversary #Artificial intelligence #Computer science #Computer security #Data modeling #Database #Divergence (linguistics) #Explainable Artificial Intelligence (XAI) #Language model #Machine learning #Memorization #Natural language processing #Scalability #Topic Modeling #Training (meteorology) #Training set
- DiLoCo: Distributed Low-Communication Training of Language Models
2023/11/14 by Arthur Douillard, Douillard, Arthur, Qixuan Feng +16 · 6 voices · 40 citations
Computer Science · Engineering · #Advanced Neural Network Applications #Artificial intelligence #Computer science #Distributed computing #Federated learning #Ferroelectric and Negative Capacitance Devices #Language model #Leverage (statistics) #Machine learning #Robustness (evolution) #Topic Modeling #Training set
- Pre-training with Synthetic Data Helps Offline Reinforcement Learning
2023/10/01 by Zecheng Wang, Wang, Zecheng, Che Wang +5 · 4 citations
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Artificial intelligence #Artificial neural network #Computer science #Engineering #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification #Machine learning #Perceptron #Reinforcement learning #Synthetic data #Training (meteorology) #Training set #Transformer
- Low-Resource Self-Supervised Learning with SSL-Enhanced TTS
2023/09/29 by Po‐Chun Hsu, Ali Elkahky, Hsu, Po-chun +15 · 2 citations
Computer Science · #Artificial intelligence #Audio and Speech Processing (eess.AS) #Computer science #Construct (python library) #FOS: Computer and information sciences #FOS: Electrical engineering #Labeled data #Machine learning #Natural Language Processing Techniques #Natural language processing #Quality (philosophy) #Resource (disambiguation) #Sound (cs.SD) #Speech Recognition and Synthesis #Speech processing #Speech recognition #Topic Modeling #Training set #electronic engineering #information engineering
- I'm Afraid I Can't Do That: Predicting Prompt Refusal in Black-Box Generative Language Models
2023/06/06 by Max Reuter, Maximilian Reuter, William B. Schulze +3 · 1 voice · 2 citations
Computer Science · #Artificial intelligence #Binary classification #Binary number #Classifier (UML) #Computer science #Discriminative model #Generative grammar #Generative model #Hate Speech and Cyberbullying Detection #Machine learning #Natural language processing #Offensive #Operations research #Support vector machine #Text Readability and Simplification #Topic Modeling #Training set
- Scaling Data-Constrained Language Models
2023/05/25 by Niklas Muennighoff, Muennighoff, Niklas, Alexander M. Rush +15 · 1 voice · 113 citations
Computer Science · Mathematics · #Artificial intelligence #Code (set theory) #Computer science #Data mining #Data set #Language model #Limit (mathematics) #Machine learning #Mathematics #Natural Language Processing Techniques #Ranging #Repetition (rhetorical device) #Scaling #Set (abstract data type) #Speech Recognition and Synthesis #The Internet #Topic Modeling #Training set #Value (mathematics) #cs.AI #cs.CL #cs.LG
- Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
2023/05/03 by Cheng-Yu Hsieh, Chun-Liang Li, Chunliang Li +18 · 5 voices · 171 citations
Computer Science · #Artificial intelligence #Benchmark (surveying) #Code (set theory) #Computer science #Distillation #Language model #Machine learning #Natural Language Processing Techniques #Programming language #Task (project management) #Text Readability and Simplification #Topic Modeling #Training set #cs.AI #cs.CL #cs.LG
- DINOv2: Learning Robust Visual Features without Supervision
2023/04/14 by Maxime Oquab, Timothée Darcet, Oquab, Maxime +50 · 5 voices · 2472 citations
Computer Science · #Advanced Neural Network Applications #Artificial intelligence #Computer science #Domain Adaptation and Few-Shot Learning #Image (mathematics) #Machine learning #Multimodal Machine Learning Applications #Pipeline (software) #Scale (ratio) #Training set
- A Note on Normalized Emergence Timing (in Pythia Language Model Evaluations)
2023/04/03 by Stella Biderman, Biderman, Stella, Hailey Schoelkopf +23 · 3 voices · 396 citations
Computer Science · Psychology · #Artificial intelligence #Code (set theory) #Computer science #Data science #Machine learning #Mathematics education #Memorization #Natural Language Processing Techniques #Programming language #Psychology #Scale (ratio) #Scaling #Set (abstract data type) #Suite #Test suite #Topic Modeling #Training (meteorology) #Training set #cs.CL
- Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection
2023/04/03 by Maxime Labonne, Seán Moran, Labonne, Maxime +2 · 2 voices · 5 citations
Computer Science · #Artificial intelligence #Baseline (sea) #Benchmarking #Computer science #F1 score #Internet Traffic Analysis and Secure E-voting #Machine learning #Naive Bayes classifier #Natural language processing #Sentence #Set (abstract data type) #Spam and Phishing Detection #Support vector machine #Topic Modeling #Training set
- Extracting Training Data from Diffusion Models
2023/01/30 by Nicholas Carlini, Carlini, Nicholas, Jamie Hayes +15 · 9 voices · 163 citations
Computer Science · #Artificial intelligence #Computer science #Computer vision #Data mining #Data science #Diffusion #Filter (signal processing) #Generative Adversarial Networks and Image Synthesis #Generative grammar #Generative model #Geography #Machine learning #Pipeline (software) #Training (meteorology) #Training set
- Generalized but not Robust? Comparing the Effects of Data Modification\n Methods on Out-of-Domain Generalization and Adversarial Robustness
2022/03/15 by Tejas Gokhale, Swaroop Mishra, Gokhale, Tejas +7 · 3 citations
Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #Adversarial system #Artificial Intelligence (cs.AI) #Artificial intelligence #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Data mining #Debiasing #Domain (mathematical analysis) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generalization #Inference #Machine Learning (cs.LG) #Machine learning #Mathematics #Multimodal Machine Learning Applications #Robustness (evolution) #Synthetic data #Training set
- Training language models to follow instructions with human feedback
2022/03/04 by Long Ouyang, Jeff Wu, Ouyang, Long +38 · 9 voices · 4022 citations
Computer Science · #Artificial intelligence #Computer science #Explainable Artificial Intelligence (XAI) #Human–computer interaction #Language model #Machine learning #Natural Language Processing Techniques #Natural language processing #Programming language #Range (aeronautics) #Reinforcement learning #Set (abstract data type) #Simple (philosophy) #Topic Modeling #Training set
- Excess Capacity and Backdoor Poisoning
2021/09/02 by Naren Sarayu Manoj, Avrim Blum, Manoj, Naren Sarayu +1 · 3 citations
Computer Science · Mathematics · #Adversarial Robustness in Machine Learning #Adversarial system #Anomaly Detection Techniques and Applications #Artificial intelligence #Backdoor #Computer science #Computer security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Generalization #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine learning #Mathematics #Privacy-Preserving Technologies in Data #Robustness (evolution) #Set (abstract data type) #Training set
- Stain-Robust Mitotic Figure Detection for the Mitosis Domain Generalization Challenge
2021/09/02 by Mostafa Jahanifar, Jahanifar, Mostafa, Adam Shephard +13 · 1 citation
Computer Science · Mathematics · #AI in cancer detection #Advanced Neural Network Applications #Artificial intelligence #Artificial neural network #Biology #Classifier (UML) #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Computer vision #FOS: Computer and information sciences #Generalizability theory #Generalization #Machine learning #Mathematics #Medical Image Segmentation Techniques #Pathology #Pattern recognition (psychology) #Perceptron #Robustness (evolution) #Stain #Test set #Training set
- Implicit Gradient Alignment in Distributed and Federated Learning
2021/06/25 by Yatin Dandi, Dandi, Yatin, Luis Barba +3 · 6 citations
Computer Science · Engineering · Mathematics · #Algorithm #Artificial intelligence #Computer science #FOS: Computer and information sciences #Generalization #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine learning #Mathematics #Obstacle #Privacy-Preserving Technologies in Data #Regularization (linguistics) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Training set
- Data Movement Is All You Need: A Case Study on Optimizing Transformers
2020/06/30 by Andrei Ivanov, Nikoli Dryden, Ivanov, Andrei +7 · 23 citations
Computer Science · Engineering · #Advanced Neural Network Applications #Artificial intelligence #Artificial neural network #Bottleneck #Computer architecture #Computer engineering #Computer science #Deep learning #Embedded system #Engineering #FOS: Computer and information sciences #Implementation #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine learning #Parallel Computing and Optimization Techniques #Software engineering #Topic Modeling #Training set #Transformer #Voltage
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