activity
20242026
most citedReflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

5 citations · 6 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

MotionCrafter: Dense Geometry and Motion Reconstruction with a 4D VAE

Ruijie Zhu, Jiahao Lu, Wenbo Hu +4

We present MotionCrafter, a framework that leverages video generators to jointly reconstruct 4D geometry and estimate dense motion from a monocular video. The key idea is a joint r…

cs.LG2025

ZeCO: Zero Communication Overhead Sequence Parallelism for Linear Attention

Yuhong Chou, Zehao Liu, Ruijie Zhu +6

Linear attention mechanisms deliver significant advantages for Large Language Models (LLMs) by providing linear computational complexity, enabling efficient processing of ultra-lon…

cs.LG2025

Scaling Linear Attention with Sparse State Expansion

Yuqi Pan, Yongqi An, Zheng Li +6

The Transformer architecture, despite its widespread success, struggles with long-context scenarios due to quadratic computation and linear memory growth. While various linear atte…

cs.LG20241 cited

MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map

Yuhong Chou, Man Yao, Kexin Wang +7

Various linear complexity models, such as Linear Transformer (LinFormer), State Space Model (SSM), and Linear RNN (LinRNN), have been proposed to replace the conventional softmax a…

cs.LG20245 cited

Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Yoel Zimmermann, Adib Bazgir, Zartashia Afzal +141

Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hyb…