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It has been said that information theory and machine learning are "two sides of the same coin" because of their close relationship. One exquisite relationship is the fundamental similarity between probabilistic...
Researchers have introduced a cutting-edge framework called MUTEX, short for "MUltimodal Task specification for robot EXecution," aimed at significantly advancing the capabilities of robots in assisting humans. The primary problem they tackle is the limitation of...
Multilingual Neural Machine Translation (MNMT) reduces deployment costs by allowing a single system to translate sentences between several source and target languages.
To gauge the...
Using talking face creation, it is possible to create lifelike video portraits of a target individual that correspond to the speech content. Given that...
Through the advancement of neural networks and end-to-end modeling, the field of voice synthesis has made significant strides during the past ten years. Currently,...
In surroundings humans have created, line segments are common and efficiently convey the underlying picture structure. They complement feature points nicely because of their...
Large-scale text-to-image models, looking at you Stable Diffusion, have dominated the machine learning space in recent months. They have shown extraordinary generation performance in...
In the latest research, Microsoft researchers developed an E5 model designed for general-purpose text embeddings. Text embeddings, which are arbitrary-length text representations in the...
Researchers at Microsoft are committed to researching ways technology may help the world's most marginalized peoples improve their human rights situations. Their expertise spans...
The methods currently used to correct systematic issues in NLP models are either fragile or time-consuming and prone to shortcuts. Humans, on the other...
Generative Adversarial Networks (or just GANs) have been widely used to generate synthetic data for different applications in recent years. The most commonly considered...
Synthetic data has frequently been used for a range of computer vision tasks, such as object identification, scene comprehension, eye tracking, hand tracking, and...
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