VQV Signal
Researchers introduced Malaria-Instruct, a curated dataset for malaria virtual screening, and systematically evaluated five open-source LLMs against classical ML models on out-of-distribution data. The study benchmarks models including Gemma-2 and LlaSMol-Mistral-7B for drug discovery tasks.
Researchers introduced Malaria-Instruct, a curated dataset for malaria virtual screening, and systematically evaluated five open-source LLMs against classical ML models on out-of-distribution data. The study benchmarks models including Gemma-2 and LlaSMol-Mistral-7B for drug discovery tasks.
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We introduce Malaria-Instruct, a curated instruction-following dataset derived from the ChEMBL Legacy Malaria corpus for Malaria virtual screening, and conduct a systematic evaluation of five open-source LLMs; Gemma-2 2B/9B, TxGemma-2B/9B, and LlaSMol-Mistral-7B, on a rigorous out-of-distribution data split....
This evaluation highlights the trade-offs in performance, scale, and resource utility of open-source LLMs in a critical biomedical application. It provides insights into how these models compare to traditional methods in malaria drug discovery.
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