Isabela Albuquerque
45 posts
@isabela_alb
Research Scientist @DeepMind. She/her. 🇧🇷
We released the first split of RepLiQA. The data is given by context-question-answer triplets, and contexts are documents concerning made-up things/people/places. As such, RepLiQA can be used for reliably testing the ability of LLMs to seek informantion on provided context.
📢 New paper out! We release RepLiQA: a Q&A dataset designed to evaluate language models in a truly unseen context. RepLiQA covers made-up entities so that knowledge obtained during training cannot be re-used to answer its questions. #LLM #Evaluation @ServiceNow @ServiceNowRSRCH
By generating synthetic image samples specific to underrepresented groups, diffusion models help medical image classifiers to achieve greater #fairness metrics across a variety of medical disciplines and demographic attributes. @OliviaW47557022, @s0f1ra nature.com/articles/s4159…
📢Mixtures of Experts unlock parameter scaling for deep RL! Adding MoEs, and in particular Soft MoEs, to value-based deep RL agents results in more parameter-scalable models. Performance keeps increasing as we increase number of experts (green line below)! 1/9
It's that time of the year once again! With @cottascience and 20+ other amazing mentors, we will have set up a simple "mentorship" program to help you get your Ph.D. application in shape. brazilians-in-ds-ml.github.io
