406 citations · 429 across the 9 of their papers we have counts for
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cs.LG2024★ 10 cited
Benchmarking large language models for materials synthesis: the case of atomic layer deposition
Angel Yanguas-Gil, Matthew T. Dearing, Jeffrey W. Elam +5
In this work we introduce an open-ended question benchmark, ALDbench, to evaluate the performance of large language models (LLMs) in materials synthesis, and in particular in the f…
cs.SE2024★ 8 cited
LASSI: An LLM-based Automated Self-Correcting Pipeline for Translating Parallel Scientific Codes
Matthew T. Dearing, Yiheng Tao, Xingfu Wu +2
This paper addresses the problem of providing a novel approach to sourcing significant training data for LLMs focused on science and engineering. In particular, a crucial challenge…