most citedEnd-to-End Crystal Structure Prediction from Powder X-Ray Diffraction

6 citations · 10 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2025

Theoretical Benefit and Limitation of Diffusion Language Model

Guhao Feng, Yihan Geng, Jian Guan +3

Diffusion language models have emerged as a promising approach for text generation. One would naturally expect this method to be an efficient replacement for autoregressive models…

cs.LG2024★ 2 cited

How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs

Guhao Feng, Kai Yang, Yuntian Gu +6

Despite the remarkable success of Transformer-based large language models (LLMs) across various domains, understanding and enhancing their mathematical capabilities remains a signi…

eess.IV2024

Knowledge-driven AI-generated data for accurate and interpretable breast ultrasound diagnoses

Haojun Yu, Youcheng Li, Nan Zhang +17

Data-driven deep learning models have shown great capabilities to assist radiologists in breast ultrasound (US) diagnoses. However, their effectiveness is limited by the long-tail…

cs.LG2024

Do Efficient Transformers Really Save Computation?

Kai Yang, Jan Ackermann, Zhenyu He +6

As transformer-based language models are trained on increasingly large datasets and with vast numbers of parameters, finding more efficient alternatives to the standard Transformer…

cs.LG2024★ 2 cited

Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness

Bohang Zhang, Jingchu Gai, Yiheng Du +3

Designing expressive Graph Neural Networks (GNNs) is a fundamental topic in the graph learning community. So far, GNN expressiveness has been primarily assessed via the Weisfeiler-…

cs.LG2024

Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation

Zhenyu He, Guhao Feng, Shengjie Luo +6

In this work, we leverage the intrinsic segmentation of language sequences and design a new positional encoding method called Bilevel Positional Encoding (BiPE). For each position,…

physics.chem-ph2024★ 6 cited

End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction

Qingsi Lai, Fanjie Xu, Lin Yao +8

Powder X-ray diffraction (PXRD) is a prevalent technique in materials characterization. While the analysis of PXRD often requires extensive human manual intervention, and most auto…