MolDA is a multimodal molecular model that uses a discrete large language diffusion backbone plus a hybrid graph encoder to achieve better global coherence and validity than autoregressive approaches.
Towards 3d molecule-text interpretation in language models
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
MolReFlect introduces a teacher-student framework that automatically creates fine-grained molecule-text alignments to achieve SOTA results on molecule-caption translation.
SciCore-Mol augments LLMs with three integrated modules for molecular perception, latent diffusion generation, and reaction reasoning, claiming an 8B open model competes with or exceeds proprietary systems on chemical tasks.
citing papers explorer
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MolDA: Molecular Understanding and Generation via Large Language Diffusion Model
MolDA is a multimodal molecular model that uses a discrete large language diffusion backbone plus a hybrid graph encoder to achieve better global coherence and validity than autoregressive approaches.
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MolReFlect: Towards In-Context Fine-grained Alignments between Molecules and Texts
MolReFlect introduces a teacher-student framework that automatically creates fine-grained molecule-text alignments to achieve SOTA results on molecule-caption translation.
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SciCore-Mol: Augmenting Large Language Models with Pluggable Molecular Cognition Modules
SciCore-Mol augments LLMs with three integrated modules for molecular perception, latent diffusion generation, and reaction reasoning, claiming an 8B open model competes with or exceeds proprietary systems on chemical tasks.