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Jialu Wu

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Book Open access Aug 2026

Caduceus: MoE Foundation Models for Unifying Biological and Natural Language

This paper introduces Caduceus, a family of MoE-enhanced foundation models built with a hierarchical pre-training paradigm to jointly integrate biological and natural language, and incorporates a multi-task instruction tuning phase, enabling robust protein parsing and natural language question answering.

Ming-Ze Yin, Yiheng Zhu, Jialu Wu et al. · 1 citation
#machine learning Open access Jun 2025

HiCLR: Knowledge-Induced Hierarchical Contrastive Learning with Retrosynthesis Prediction Yields a Reaction Foundation Model

HiCLR is the first foundation model that can be broadly applied to various synthesis-related tasks, and it achieves state-of-the-art performance in reaction classification, reaction condition recommendation, reaction yield prediction, synthesis planning, and even molecular property prediction.

Jialu Wu, Yiheng Zhu, Xiaorui Wang et al. · 0 citations
#natural language process... Book Open access Aug 2026

Caduceus: MoE Foundation Models for Unifying Biological and Natural Language

This paper introduces Caduceus, a family of MoE-enhanced foundation models built with a hierarchical pre-training paradigm to jointly integrate biological and natural language, and incorporates a multi-task instruction tuning phase, enabling robust protein parsing and natural language question answering.

Mingze Yin, Yiheng Zhu, Jialu Wu et al. · 0 citations

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