Meta Research

In this paper, we present AGRoL, a novel conditional diffusion model specially purposed to track full bodies given sparse upper-body tracking signals. Our model uses a simple...

This paper presents an application of these models in an actual data center in the United States with a successful prediction of the thermal behavior within 1 degree Fahrenheit...

This is the first work to report on inferential testing at scale in industry. Specifically, it reports the experience of automated testing of integrity systems at Meta. We built...

In this paper we highlight open research problems and challenges from an industrial perspective. This perspective draws on our experience at Meta Platforms, which has been...

We reduce the quantization loss of a given image representation by making imperceptible changes to the image before its release. The loss is back-propagated through the deep...

In this paper we present HierCat, the query categorization system at Facebook Marketplace. HierCat addresses these challenges by leveraging multi-task pre-training of...

In this paper we present Que2Engage, a search EBR system designed to bridge the gap between retrieval and ranking for better end-to-end optimization. Que2Engage takes a...

In this work, we introduce CAM2, a conformity-aware multi-task ranking model to serve relevant items to users on one of the largest industrial recommendation platforms.

We introduce Continual Subspace of Policies (CSP), a new approach that incrementally builds a subspace of policies for training a reinforcement learning agent on a sequence of...

We propose a novel OS-level application-transparent page placement mechanism (TPP) for CXL-enabled memory. TPP employs a lightweight mechanism to identify and place hot/cold...