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.LG2024★ 1 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.LG2024★ 5 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…