Researchers increasingly fine-tune models on synthetic data, but generated datasets may not be sufficiently diverse. New work used agentic workflows to produce diverse synthetic datasets.
Researchers increasingly fine-tune models on synthetic data, but generated datasets may not be sufficiently diverse. New work used agentic workflows to produce diverse synthetic datasets.
Previous systems that produce a talking-head video from a photo and a spoken-word audio clip animate the lips and other parts of the face separately.
Previous systems that produce a talking-head video from a photo and a spoken-word audio clip animate the lips and other parts of the face separately.
Large language models can produce output that’s convincing but false. Researchers proposed a way to identify such hallucinations.
Large language models can produce output that’s convincing but false. Researchers proposed a way to identify such hallucinations.
The word “open” can mean many things with respect to AI. A new paper outlines the variations and ranks popular models for openness.
The word “open” can mean many things with respect to AI. A new paper outlines the variations and ranks popular models for openness.
Published in mid-2022, DreamBooth enables Stable Diffusion to depict variations on a given subject; say, a particular dog and the same dog with angel wings or wearing a chef’s hat.
Published in mid-2022, DreamBooth enables Stable Diffusion to depict variations on a given subject; say, a particular dog and the same dog with angel wings or wearing a chef’s hat.
Low-rank adaptation (LoRA) reduces memory requirements when fine-tuning large language models, but it isn’t as conducive to pretraining.
Low-rank adaptation (LoRA) reduces memory requirements when fine-tuning large language models, but it isn’t as conducive to pretraining.
The technique of model merging combines separate models into a single, more capable model without further training, but it requires expertise and manual effort. Researchers automated the process.
The technique of model merging combines separate models into a single, more capable model without further training, but it requires expertise and manual effort. Researchers automated the process.
BERT, a large language model released in 2018 and built upon the then-new transformer architecture, marked a paradigm shift in AI.
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