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201

Toward training NLP models to take into account privacy leakages
Berthelier, Gaspard ; Boutet, Antoine ; Richard, Antoine ; et al.
BigData 2023 - IEEE International Conference on Big Data. :1-9

Sorrento, Italy NLP models Privacy Membership Inference Counterfactual Memorisat... Data Extraction …
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202

Slight Corruption in Pre-training Data Makes Better Diffusion Models
Chen, Hao ; Han, Yujin ; Misra, Diganta ; et al.

Computer Science - Compu... Computer Science - Artif... Computer Science - Machi...
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203

Reducing the Feature Distance between Real and Synthetic Data for Training Safeguards-Relevant Computer Vision Models.
Marshall, Matthew R. ; Gastelum, Zoe N. ; Shead, Timothy M.
Journal of the Institute of Nuclear Materials Management. 2025 3rd Quarter, Vol. 52 Issue 3, p30-42. 13p.

Computer vision Nuclear nonproliferation Machine learning Data augmentation Metadata Empirical research …
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204

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205

Deep learning-based error recognition in manual cable assembly using synthetic training data
Conrad, Jonas ; Stauffer, Tobias ; Meng, Xuanting ; et al.
In Procedia CIRP 2024 128:239-244

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206

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207

ROC curves for machine learning model performance on training data.
Hiroyuki Akamine ; Akiyuki Uzawa ; Satoshi Kuwabara ; et al.

Medicine Biotechnology Science Policy Infectious Diseases using 414 registrants potentially guiding clin... …
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208

A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of Transformer Textual Models
Dang, Cuong ; Le, Dung D. ; Le, Thai
Findings of the Association for Computational Linguistics ACL 2024. :13475-13491

FOS: Computer and inform... Computer Science - Machi... Computer Science - Compu... Computer Science - Crypt... Computation and Language... Cryptography and Securit... …
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209

Deep Learning of Crystalline Defects from TEM images: A Solution for the Problem of' Never Enough Training Data'
Govind, Kishan ; Oliveros, Daniela ; Dlouhy, Antonin ; et al.
Machine Learning: Science and Technology, 2023, ⟨10.48550/arXiv.2307.06322⟩

FOS: Physical sciences FOS: Computer and inform... Materials Science (cond-... Computer Vision and Patt... crystal defect dislocation …
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210

Special Characters Attack: Toward Scalable Training Data Extraction From Large Language Models
Bai, Yang ; Pei, Ge ; Gu, Jindong ; et al.

Computer Science - Crypt... Computer Science - Artif... Computer Science - Compu... Computer Science - Machi...
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211

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213

Deep learning-based object detection of offshore platforms on Sentinel-1 imagery and the impact of synthetic training data.
Spanier, Robin ; Hoeser, Thorsten ; Kuenzer, Claudia
International Journal of Remote Sensing. Jan2026, p1-25. 25p. 9 Illustrations.

PERSIAN Gulf GULF of Mexico DEEP learning OFFSHORE structures DETECTION algorithms REMOTE-sensing images …
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214

Training Set Class Distribution Analysis for Deep Learning Model - Application to Cancer Detection
Reshma, Ismat Ara ; Gaspard, Margot ; Franchet, Camille ; et al.
1st International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI 2019). :123-127

Barcelona, Spain Class-biased training Deep learning Image segmentation and c... Medical information retr... [INFO.INFO-AI]Computer S... …
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215

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216

ATSumm: Auxiliary information enhanced approach for abstractive disaster tweet summarization with sparse training data
Garg, Piyush Kumar ; Chakraborty, Roshni ; Dandapat, Sourav Kumar
In Knowledge-Based Systems 28 February 2025 311

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217

Generative adversarial network based synthetic data training model for lightweight convolutional neural networks
Rather, Ishfaq Hussain ; Kumar, Sushil
Multimedia Tools and Applications: An International Journal. 83(2):6249-6271

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218

Improving Reward Estimation in Goal-Conditioned Imitation Learning with Counterfactual Data and Structural Causal Models
Jabri, Mohamed Khalil ; Papadakis, Panagiotis ; Abbasnejad, Ehsan ; et al.
20th International Conference on Informatics in Control. :329-337

Rome, Italy Imitation Learning Causality Structural Causal Models Counterfactual Reasoning [STAT.ML]Statistics [sta... …
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219

Extracting Training Data from Document-Based VQA Models
Pinto, Francesco ; Rauschmayr, Nathalie ; Tramèr, Florian ; et al.

Computer Science - Compu... Computer Science - Machi... I.2.7 I.2.10 K.4.1
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220

Bipolar augmentation: Lightweight artificial intelligence model training for anomaly detection under color cast scenarios
Lin, Yu-Hsun ; Lin, Yu-Mo
In Engineering Applications of Artificial Intelligence 1 April 2025 145

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