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Self-Supervised Learning and Pre-training: Training...

Modern machine learning systems thrive on data,...

Self-Supervised Learning and Pre-training: Training Models Using Automatically Generated Supervisory Signals

Modern machine learning systems thrive on data, but labelled data is often expensive, slow to collect, and limited in scope. This constraint has pushed researchers to explore approaches that can learn meaningful patterns without relying heavily on human annotation. Self-supervised learning has emerged as a powerful solution to this challenge. By generating supervisory signals directly from raw data, models can learn useful representations that transfer effectively to downstream tasks. This approach has become a cornerstone of pre-training strategies across natural language processing, computer vision, and speech recognition, and it...

Self-Supervised Learning and...

Modern machine learning systems thrive on data, but labelled data is often expensive, slow to collect, and limited in scope. This constraint has pushed...
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