Reagent Prediction
3 papers with code • 1 benchmarks • 0 datasets
Reagent prediction endeavors to ascertain the suitable catalysts, solvents, or ancillary substances required for a specific chemical reaction. This endeavor facilitates chemists in uncovering novel reaction types and mechanisms, identifying more optimal or eco-friendly reaction conditions, and ultimately streamlining the comprehensive chemical process to attain maximal cost-effectiveness and environmental stewardship.
Benchmarks
These leaderboards are used to track progress in Reagent Prediction
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Most implemented papers
Mol-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.
BioT5+: Towards Generalized Biological Understanding with IUPAC Integration and Multi-task Tuning
QizhiPei/BioT5
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However, previous efforts like BioT5 faced challenges in generalizing across diverse tasks and lacked a nuanced understanding of molecular structures, particularly in their textual representations (e. g., IUPAC).
A Self-feedback Knowledge Elicitation Approach for Chemical Reaction Predictions
ai-hpc-research-team/slm4crp
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The task of chemical reaction predictions (CRPs) plays a pivotal role in advancing drug discovery and material science.
