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Book Open access Aug 2026

UniEdit: A Graph-based MoE Alternative to Sequence Generation for Molecular Editing

This paper proposes UniEdit, a Unified Graph-based Mixture-of-Experts (MoE) Molecular Editing model that offers a robust alternative to LLMs and incorporates a Mixture-of-Experts architecture that dynamically routes tasks to specialized components.

Jiajun Yu, Zhihao Wu, Yizhen Zheng 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
Preprint Aug 2026

Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language

Transformer models have revolutionized natural language processing (NLP), and text-based molecular representations like SMILES have successfully extended these architectures to chemistry. However, domain-adaptive pre-training often causes models to overfit to chemical syntax, catastrophically forgetting their foundatio...

David Ming Segura, Jeremy Goumaz, Joshua W. Sin et al. · 1 citation
Aug 2026

Speaking the Native Language of LLMs: A Discrete Architecture for Molecular Comprehension.

MolLingua, a token-centric, dual-modal framework designed for native molecular understanding, uses a dual-branch Residual Vector Quantization engine to discretize heterogeneous, high-dimensional spatial 2D and 3D features into compact code sequences rather than relying solely on continuous projections.

Haoyang Liu, Xikang Feng, Fei Guo et al. · 0 citations
Open access Jul 2026

Navigating chemical-linguistic sharing space with heterogeneous molecular encoding

HME is presented, a framework that combines multiple views of molecules to improve molecular understanding and design and enables bidirectional navigation of the chemical-linguistic space, achieving consistent improvements across molecular comprehension and design tasks over strong baselines.

Liuzhenghao Lv, Hao Li, Yu Wang et al. · 0 citations
Jul 2026

Beyond Scale and Generation: Understanding Language Model-based Entity Matching

The factors underlying performance differences across matcher architectures are clarified and motivate future research and benchmark designs that better disentangle architectural choices from model-level factors while explicitly evaluating distribution shift and cross-dataset transferability.

Zeyu Zhang, Xue Li, Iacer Calixto et al. · 0 citations

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