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Found 5 papers, 1 papers with code
Latent Representation Matters: Human-like Sketches in One-shot Drawing Tasks
Humans can effortlessly draw new categories from a single exemplar, a feat that has long posed a challenge for generative models.
eXmY: A Data Type and Technique for Arbitrary Bit Precision Quantization
For example, it seamlessly supports 3, 5, 6, 7, 9 bit formats.
COVID-19 Vaccine Misinformation in Middle Income Countries
This paper introduces a multilingual dataset of COVID-19 vaccine misinformation, consisting of annotated tweets from three middle-income countries: Brazil, Indonesia, and Nigeria.
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior
We call these models Large Content and Behavior Models (LCBMs).
Neural Feature-Adaptation for Symbolic Predictions Using Pre-Training and Semantic Loss
Real data is often imperfect meaning that even if the symbolic theory remains unchanged, we may still need to address the problem of mapping raw data to high-level symbols, each time there is a change in the data acquisition environment or equipment.
