Microsoft Research presents Lens, a text-to-image model with just 3.8 billion parameters that matches much larger rivals on benchmarks, at a fraction of the training cost. The secret sauce: 800 million detailed image captions generated by GPT-4.1 instead of vague web alt-text. Code and weights are o...
Microsoft Research presents Lens, a text-to-image model with just 3.8 billion parameters that matches much larger rivals on benchmarks, at a fraction of the training cost. The secret sauce: 800 million detailed image captions generated by GPT-4.1 instead of vague web alt-text. Code and weights are openly available under an open-source license. The article Microsoft Research's Lens proves detailed captions matter more than raw scale for training efficient image generators appeared first on The Decoder .
Microsoft Research presents Lens, a text to image model with just 3.8 billion parameters that matches much larger rivals on benchmarks, at a fraction of the training cost.
The secret sauce: 800 million detailed image captions generated by GPT 4.1 instead of vague web alt text.
Code and weights are openly available under an open source license.
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