Assessing the Extrapolation Capability of Template-Free Retrosynthesis Models
Not on the map. Why?
Abstract (arXiv)
Despite the acknowledged capability of template-free models in exploring unseen reaction spaces compared to template-based models for retrosynthesis prediction, their ability to venture beyond established boundaries remains relatively uncharted. In this study, we empirically assess the extrapolation capability of state-of-the-art template-free models by meticulously assembling an extensive set of out-of-distribution (OOD) reactions. Our findings demonstrate that while template-free models exhibit potential in predicting precursors with novel synthesis rules, their top-10 exact-match accuracy in OOD reactions is strikingly modest (< 1%). Furthermore, despite the capability of generating novel reactions, our investigation highlights a recurring issue where more than half of the novel reactions predicted by template-free models are chemically implausible. Consequently, we advocate for the future development of template-free models that integrate considerations of chemical feasibility when navigating unexplored regions of reaction space.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 7 of its 25 references that are in the map. First posted on arXiv 29 Feb 2024.
Builds on
7 of 25 references.
References · 7
- 2017Attention Is All You Needcited by 60,361
- 2018Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Predictioncited by 229
- 2020Retrosynthesis Prediction with Conditional Graph Logic Networkcited by 104
- 2017Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Networkcited by 103
- 2017Retrosynthetic reaction prediction using neural sequence-to-sequence modelscited by 86
- 2021Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction predictioncited by 68
- 2022Root-aligned SMILES: A Tight Representation for Chemical Reaction Predictioncited by 51
Built on by
Citing papers per year: 2024: 1; 2025: 2.
3 papers.