[Paper] Word Frequency Counting Based on Serverless MapReduce
With the increasing demand for high-performance and high-efficiency computing, cloud computing, especially serverless computing, has gradually become a research...
With the increasing demand for high-performance and high-efficiency computing, cloud computing, especially serverless computing, has gradually become a research...
Human biological systems sustain life through extraordinary resilience, continually detecting damage, orchestrating targeted responses, and restoring function t...
In recent decades, the RAFT distributed consensus algorithm has become a main pillar of the distributed systems ecosystem, ensuring data consistency and fault t...
In vehicle production factories, the vehicle painting process employs multiple robotic arms to simultaneously apply paint to car bodies advancing along a convey...
Deep neural network-based classifiers are prone to errors when processing adversarial examples (AEs). AEs are minimally perturbed input data undetectable to hum...
The rapid growth of artificial intelligence (AI) has brought novel data processing and generative capabilities but also escalating energy requirements. This cha...
The increasing complexity and interconnectedness of systems across various fields have led to a growing interest in studying complex networks, particularly Scal...
We present SpaceTimePilot, a video diffusion model that disentangles space and time for controllable generative rendering. Given a monocular video, SpaceTimePil...
Recent advances in 3D reconstruction have achieved remarkable progress in high-quality scene capture from dense multi-view imagery, yet struggle when input view...
Humanoid robots hold great promise for operating in human-centric environments, yet achieving robust whole-body coordination across the head, hands, and legs re...
We present Edit3r, a feed-forward framework that reconstructs and edits 3D scenes in a single pass from unposed, view-inconsistent, instruction-edited images. U...
High-stakes decision making involves reasoning under uncertainty about the future. In this work, we train language models to make predictions on open-ended fore...