33 citations · 60 across the 5 of their papers we have counts for
5 papers
AOCI: Symbolic-Semantic Indexing for Practical Repository-Scale Code Understanding with LLMs
Jinshi Liu, Hanying Zuo, Congyin Cao +3
Large language models struggle with understanding codebases beyond a certain scale -- repositories with hundreds of thousands of lines of code. Existing methods -- retrieval, summa…
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…
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…
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…
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…