activity
20232026
most citedDifficulty in chirality recognition for Transformer architectures learning chemical structures from string

42 citations · 49 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

From Syntax to Semantics: Unveiling the Emergence of Chirality in SMILES Translation Models

Zehao Li, Yasuhiro Yoshikai, Shumpei Nemoto +2

Understanding how chemical language models (CLMs) learn chemical meaning from molecular string representations, rather than only surface-level string patterns, is an important ques…

q-bio.QM2025

Exploring Multi-Objective Trade-offs in Reference Compound Selection for Validation Studies of Toxicity Assays

Yohei Ohto, Tadahaya Mizuno, Yasuhiro Yoshikai +2

In chemical safety assessment, validation studies rely on reference compound lists to evaluate the applicability of alternative methods prior to regulatory acceptance. These lists…

q-bio.QM2025★ 2 cited

Notation-level confounding: When inconsistent molecular notations mislead chemical language models

Yosuke Kikuchi, Yasuhiro Yoshikai, Shumpei Nemoto +4

Chemical language models (CLMs) are increasingly used for molecular design and property prediction. Because these models learn from textual encodings of molecules, differences in h…

q-bio.BM2024★ 5 cited

A novel molecule generative model of VAE combined with Transformer for unseen structure generation

Yasuhiro Yoshikai, Tadahaya Mizuno, Shumpei Nemoto +1

Recently, molecule generation using deep learning has been actively investigated in drug discovery. In this field, Transformer and VAE are widely used as powerful models, but they…

cs.LG2023★ 42 cited

Difficulty in chirality recognition for Transformer architectures learning chemical structures from string

Yasuhiro Yoshikai, Tadahaya Mizuno, Shumpei Nemoto +1

Recent years have seen rapid development of descriptor generation based on representation learning of extremely diverse molecules, especially those that apply natural language proc…