9 citations · 17 across the 6 of their papers we have counts for
6 papers
SynCraft: Guiding Large Language Models to Predict Edit Sequences for Molecular Synthesizability Optimization
Junren Li, Luhua Lai
Generative artificial intelligence has revolutionized the exploration of chemical space, yet a critical bottleneck remains that a substantial fraction of generated molecules is syn…
A Scientific Reasoning Model for Organic Synthesis Procedure Generation
Guoqing Liu, Junren Li, Zihan Zhao +7
Solving computer-aided synthesis planning is essential for enabling fully automated, robot-assisted synthesis workflows and improving the efficiency of drug discovery. A key challe…
SUPERChem: A Multimodal Reasoning Benchmark in Chemistry
Zehua Zhao, Zhixian Huang, Junren Li +28
Current benchmarks for evaluating the chemical reasoning capabilities of Large Language Models (LLMs) are limited by oversimplified tasks, lack of process-level evaluation, and mis…
Chemist-aligned retrosynthesis by ensembling diverse inductive bias models
Krzysztof Maziarz, Guoqing Liu, Hubert Misztela +8
Chemical synthesis remains a critical bottleneck in the discovery and manufacture of functional small molecules. AI-based synthesis planning models could be a potential remedy to f…
Retro-BLEU: Quantifying Chemical Plausibility of Retrosynthesis Routes through Reaction Template Sequence Analysis
Junren Li, Lei Fang, Jian-Guang Lou
Computer-assisted methods have emerged as valuable tools for retrosynthesis analysis. However, quantifying the plausibility of generated retrosynthesis routes remains a challenging…
Leveraging Reaction-aware Substructures for Retrosynthesis Analysis
Lei Fang, Junren Li, Ming Zhao +2
Retrosynthesis analysis is a critical task in organic chemistry central to many important industries. Previously, various machine learning approaches have achieved promising result…