ALMs unify pretrained atomistic encoder, LLM, and denoising diffusion via continuous projectors and staged training to reach SOTA on text-conditioned crystal prediction and de novo generation.
Selfies: a robust representation of semantically constrained graphs with an example application in chemistry
3 Pith papers cite this work. Polarity classification is still indexing.
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S^2-Bench is a new one-to-many benchmark for natural language-driven molecule generation with three tasks, and OpenMolIns is an instruction dataset enabling Llama3.1-8B to outperform GPT-4o and Claude-3.5 on it.
CoRe-Gen reaches new state-of-the-art exact-match accuracy on the NPLIB1 benchmark for de novo molecular structure generation from mass spectra by using synthetic pretraining, frequency-aware corruption, and structure-aware decoding to close the gap between clean training data and noisy deployment.
citing papers explorer
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Atomistic Language Models Understand and Generate Materials
ALMs unify pretrained atomistic encoder, LLM, and denoising diffusion via continuous projectors and staged training to reach SOTA on text-conditioned crystal prediction and de novo generation.
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Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation
S^2-Bench is a new one-to-many benchmark for natural language-driven molecule generation with three tasks, and OpenMolIns is an instruction dataset enabling Llama3.1-8B to outperform GPT-4o and Claude-3.5 on it.
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CoRe-Gen: Robust Spectrum-to-Structure Generation under Imperfect Fingerprint Conditions
CoRe-Gen reaches new state-of-the-art exact-match accuracy on the NPLIB1 benchmark for de novo molecular structure generation from mass spectra by using synthetic pretraining, frequency-aware corruption, and structure-aware decoding to close the gap between clean training data and noisy deployment.