320 citations · 1.4k across the 14 of their papers we have counts for
15 papers
Cosmos 3: Omnimodal World Models for Physical AI
NVIDIA, :, Aditi +293
We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…
Decentralised possibilistic inference with applications to target tracking
Jeremie Houssineau, Han Cai, Murat Uney +1
Fusing and sharing information from multiple sensors over a network is a challenging task, partly due to the absence of a foundational rule for fusing probability distributions tha…
EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction
Han Cai, Junyan Li, Muyan Hu +2
High-resolution dense prediction enables many appealing real-world applications, such as computational photography, autonomous driving, etc. However, the vast computational cost ma…
TinyTL: Reduce Activations, Not Trainable Parameters for Efficient On-Device Learning
Han Cai, Chuang Gan, Ligeng Zhu +1
On-device learning enables edge devices to continually adapt the AI models to new data, which requires a small memory footprint to fit the tight memory constraint of edge devices.…
Once-for-All: Train One Network and Specialize it for Efficient Deployment
Han Cai, Chuang Gan, Tianzhe Wang +2
We address the challenging problem of efficient inference across many devices and resource constraints, especially on edge devices. Conventional approaches either manually design o…
Design Automation for Efficient Deep Learning Computing
Song Han, Han Cai, Ligeng Zhu +4
Efficient deep learning computing requires algorithm and hardware co-design to enable specialization: we usually need to change the algorithm to reduce memory footprint and improve…