activity
20222024
most citedDARWIN Series: Domain Specific Large Language Models for Natural Science

33 citations · 62 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2024★ 4 cited

DARWIN 1.5: Large Language Models as Materials Science Adapted Learners

Tong Xie, Yuwei Wan, Yixuan Liu +8

Materials discovery and design aim to find compositions and structures with desirable properties over highly complex and diverse physical spaces. Traditional solutions, such as hig…

cs.CL2024★ 5 cited

SciQAG: A Framework for Auto-Generated Science Question Answering Dataset with Fine-grained Evaluation

Yuwei Wan, Yixuan Liu, Aswathy Ajith +6

We introduce SciQAG, a novel framework for automatically generating high-quality science question-answer pairs from a large corpus of scientific literature based on large language…

cs.CL2023★ 33 cited

DARWIN Series: Domain Specific Large Language Models for Natural Science

Tong Xie, Yuwei Wan, Wei Huang +9

Emerging tools bring forth fresh approaches to work, and the field of natural science is no different. In natural science, traditional manual, serial, and labour-intensive work is…

cs.CL2023★ 18 cited

Large Language Models as Master Key: Unlocking the Secrets of Materials Science with GPT

Tong Xie, Yuwei Wan, Wei Huang +8

The amount of data has growing significance in exploring cutting-edge materials and a number of datasets have been generated either by hand or automated approaches. However, the ma…

cond-mat.mtrl-sci2022★ 2 cited

Interdisciplinary Discovery of Nanomaterials Based on Convolutional Neural Networks

Tong Xie, Yuwei Wan, Weijian Li +7

The material science literature contains up-to-date and comprehensive scientific knowledge of materials. However, their content is unstructured and diverse, resulting in a signific…