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20222026
most citedMolTRES: Improving Chemical Language Representation Learning for Molecular Property Prediction

1 citations · 1 across the 11 of their papers we have counts for

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cs.CL2025

Handling Korean Out-of-Vocabulary Words with Phoneme Representation Learning

Nayeon Kim, Eojin Jeon, Jun-Hyung Park +1

In this study, we introduce KOPL, a novel framework for handling Korean OOV words with Phoneme representation Learning. Our work is based on the linguistic property of Korean as a…

cs.CL2025

Incorporating Domain Knowledge into Materials Tokenization

Yerim Oh, Jun-Hyung Park, Junho Kim +2

While language models are increasingly utilized in materials science, typical models rely on frequency-centric tokenization methods originally developed for natural language proces…