Forward reaction prediction
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Benchmarks
Mol-Instruction
Most implemented
Papers
Augmenting Molecular Language Models with Local $n$-gram Memory
Transformer-based language models for SMILES strings suffer from a locality gap: standard character-level tokenization fragments chemically meaningful motifs, forcing models to repeatedly learn local syntax at the expens…
Unconditional Molecule GenerationForward reaction predictionSingle-step retrosynthesisModular Multi-Task Learning for Chemical Reaction Prediction
Adapting large language models (LLMs) trained on broad organic chemistry to smaller, domain-specific reaction datasets is a key challenge in chemical and pharmaceutical R&D. Effective specialisation requires learning new…
parameter-efficient fine-tuningChemical Reaction PredictionForward reaction predictionMulti-Task LearningEvaluating Molecule Synthesizability via Retrosynthetic Planning and Reaction Prediction
A significant challenge in wet lab experiments with current drug design generative models is the trade-off between pharmacological properties and synthesizability. Molecules predicted to have highly desirable properties …
Drug DesignDrug DiscoveryForward reaction predictionA Self-feedback Knowledge Elicitation Approach for Chemical Reaction Predictions
The task of chemical reaction predictions (CRPs) plays a pivotal role in advancing drug discovery and material science. However, its effectiveness is constrained by the vast and uncertain chemical reaction space and chal…
Chemical Reaction PredictionDrug DiscoveryForward reaction predictionLanguage Modeling+5BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
Recent research trends in computational biology have increasingly focused on integrating text and bio-entity modeling, especially in the context of molecules and proteins. However, previous efforts like BioT5 faced chall…
Drug DiscoveryForward reaction predictionMolecule CaptioningReagent Prediction+2Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models
Large Language Models (LLMs), with their remarkable task-handling capabilities and innovative outputs, have catalyzed significant advancements across a spectrum of fields. However, their proficiency within specialized do…
Catalytic activity predictionChemical-Disease Interaction ExtractionChemical Entity RecognitionChemical-Protein Interaction Extraction+12