The integration of biomolecular modeling with natural language (BL) has emerged as a
promising interdisciplinary area at the intersection of artificial intelligence, chemistry and …

After ChatGPT was released, large language models (LLMs) became more popular.
Academicians use ChatGPT or LLM models for different purposes, and the use of ChatGPT …

Understanding biological processes, drug development, and biotechnological
advancements requires detailed analysis of protein structures and sequences, a task in …

Humankind's understanding of the world is fundamentally linked to our perception and
cognition, with\emph {human languages} serving as one of the major carriers of\emph {world …

Multimodal Large Language Models (MLLMs) have seen growing adoption across various
scientific disciplines. These advancements encourage the investigation of molecule-text …

Understanding and designing biomolecules, such as proteins and small molecules, is
central to advancing drug discovery, synthetic biology, and enzyme engineering. Recent …

Large Language Models (LLMs) have achieved remarkable performance in multiple Natural
Language Processing (NLP) tasks. Under the premise that protein sequences constitute the …

The design of porous materials with user-desired properties has been a great interest for the
last few decades. However, the flexibility of target properties has been highly limited, and …

In recent years, large language models (LLMs) have demonstrated significant success in
performing varied natural language tasks such as language translation, question-answering …

Current Large Language Models (LLMs) for understanding proteins primarily treats amino
acid sequences as a text modality. Meanwhile, Protein Language Models (PLMs), such as …