A major methodological concern with language models pretrained on a broad swath of internet data, particularly large models with the capacity to memorize vast amounts of content, is potential contamination of downstream tasks by having their test or development sets inadvertently seen during pre-trainin...
Private data is often scattered throughout the data sets used to train LLMs, many of which are scraped off the open internet. The more often those personal bits of information appear in the training data, the more likely the model is to memorize them, and the stronger the association become...
particularly large models with the capacity to memorize vast amounts of content, is potential contamination of downstream tasks by having their test or development sets inadvertently seen during pre-training. To reduce such contamination, we searched for and attempted to remove any overlaps ...
A major methodological concern with language models pretrained on a broad swath of internet data, particularly large models with the capacity to memorize vast amounts of content, is potential contamination of downstream tasks by having their test or development sets inadvertently seen during pre-trainin...
A major methodological concern with language models pretrained on a broad swath of internet data, particularly large models with the capacity to memorize vast amounts of content, is potential contamination of downstream tasks by having their test or development sets inadvertently seen during pre-trainin...
these models can learn from exemplars. So, my hope is that it changes some people's views about in-context learning," Akyürek says. "These models are not as dumb as people think. They don't just memorize these tasks. They can learn new tasks, and we have shown how that can be ...
A major methodological concern with language models pretrained on a broad swath of internet data, particularly large models with the capacity to memorize vast amounts of content, is potential contamination of downstream tasks by having their test or development sets inadvertently seen during pre-trainin...
That is its main advantage over previous generations of chatbots, which required users to memorize command patterns or programming languages to interact with them. When you ask GPT-3 how the weather is today, it will be able to give you an answer by examining the question’s context. That ...
A major methodological concern with language models pretrained on a broad swath of internet data, particularly large models with the capacity to memorize vast amounts of content, is potential contamination of downstream tasks by having their test or development sets inadvertently seen during pre-trainin...
A major methodological concern with language models pretrained on a broad swath of internet data, particularly large models with the capacity to memorize vast amounts of content, is potential contamination of downstream tasks by having their test or development sets inadvertently seen during pre-trainin...