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...
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...
In this paper, we present the Carbon Explorer framework to analyze the solution space. We use Carbon Explorer to balance tradeoffs between operational and embodied carbon...
We propose Accountable JS, a browser extension and opt-in protocol for accountable delivery of active content on a web page. We prototype our protocol, formally model its...
We first present three real-world case studies from which we can glean practical insights unknown or neglected in research. Next we analyze all adversarial ML papers recently...
We present MultiAct, the first framework to generate long-term 3D human motion from multiple action labels. MultiAct takes account of both action and motion conditions with a...
This paper explores a SI virtuous cycle workflow to fill the gap. The proposed SI workflow significantly improved the measurement to simulation correlation in terms of eye...
This work designs a method to estimate the item-level effects from the causal perspective. We resort to causal graphs to characterize the average treatment effect of...
This work is devoted to presenting a critical assessment by systematically examining complex-valued DNNs against their real-valued counterparts. Specifically, we investigate...
We address this dilemma by introducing an online backfilling algorithm, which enables us to achieve a progressive performance improvement during the backfilling process while...
This paper describes how we transformed the legacy data lakehouse stack at Meta to adapt to the new realities through a large cross-organizational effort called Shared Foundations.