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20242026
most citedPrototypical Transformer as Unified Motion Learners

8 citations · 11 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024★ 3 cited

Visual Fourier Prompt Tuning

Runjia Zeng, Cheng Han, Qifan Wang +5

With the scale of vision Transformer-based models continuing to grow, finetuning these large-scale pretrained models for new tasks has become increasingly parameter-intensive. Visu…

physics.comp-ph2024

Diff-PIC: Revolutionizing Particle-In-Cell Nuclear Fusion Simulation with Diffusion Models

Chuan Liu, Chunshu Wu, Shihui Cao +8

The rapid development of AI highlights the pressing need for sustainable energy, a critical global challenge for decades. Nuclear fusion, generally seen as an ultimate solution, ha…

cs.LG2024

Inertial Confinement Fusion Forecasting via Large Language Models

Mingkai Chen, Taowen Wang, Shihui Cao +10

Controlled fusion energy is deemed pivotal for the advancement of human civilization. In this study, we introduce , a novel integration of Large Language Models (…

cs.LG2024

Accelerating Communication in Deep Learning Recommendation Model Training with Dual-Level Adaptive Lossy Compression

Hao Feng, Boyuan Zhang, Fanjiang Ye +9

DLRM is a state-of-the-art recommendation system model that has gained widespread adoption across various industry applications. The large size of DLRM models, however, necessitate…

cs.CV2024★ 8 cited

Prototypical Transformer as Unified Motion Learners

Cheng Han, Yawen Lu, Guohao Sun +9

In this work, we introduce the Prototypical Transformer (ProtoFormer), a general and unified framework that approaches various motion tasks from a prototype perspective. ProtoForme…