Papers › LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction

LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction

31 Oct 2024arXiv:2411.00177archive 2025-07-28

Andre Niyongabo Rubungo, Kangming Li, Jason Hattrick-Simpers, Adji Bousso Dieng

Large language models (LLMs) are increasingly being used in materials science. However, little attention has been given to benchmarking and standardized evaluation for LLM-based materials property prediction, which hinders progress. We present LLM4Mat-Bench, the largest benchmark to date for evaluating the performance of LLMs in predicting the properties of crystalline materials. LLM4Mat-Bench contains about 1.9M crystal structures in total, collected from 10 publicly available materials data sources, and 45 distinct properties. LLM4Mat-Bench features different input modalities: crystal composition, CIF, and crystal text description, with 4.7M, 615.5M, and 3.1B tokens in total for each modality, respectively. We use LLM4Mat-Bench to fine-tune models with different sizes, including LLM-Prop and MatBERT, and provide zero-shot and few-shot prompts to evaluate the property prediction capabilities of LLM-chat-like models, including Llama, Gemma, and Mistral. The results highlight the challenges of general-purpose LLMs in materials science and the need for task-specific predictive models and task-specific instruction-tuned LLMs in materials property prediction.

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extract_ans_from_chat_llm vertaix/llm4mat-bench/code/llama/llama_inference.py official repository ran · our draft was wrong fingerprinted no licence file found · pointer only · 398618b957273bc6 · report
extract_ans_from_next_token_llm vertaix/llm4mat-bench/code/llama/llama_inference.py official repository ran · our draft was wrong fingerprinted no licence file found · pointer only · c3ac3f45dbcaa8c0 · report
readJSON vertaix/llm4mat-bench/code/llama/llama_inference.py official repository ran · our draft was wrong no licence file found · pointer only · e4367e1bb4066106 · report
evaluate vertaix/llm4mat-bench/code/llmprop_and_matbert/evaluate.py official repository unverified no licence file found · pointer only · 3de2652a4ecfff48 · report

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BenchmarkingPredictionProperty Prediction

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