The year 2023 marked a significant surge in the exploration of applying large language
model chatbots, notably Chat Generative Pre‐trained Transformer (ChatGPT), across …

Efficient molecular modeling and design are crucial for the discovery and exploration of
novel molecules, and the incorporation of deep learning methods has revolutionized this …

Large Language Models (LLMs) have emerged as a transformative power in enhancing
natural language comprehension, representing a significant stride toward artificial general …

Recently, the impressive performance of large language models (LLMs) on a wide range of
tasks has attracted an increasing number of attempts to apply LLMs in drug discovery …

Deep learning has become ubiquitous in drug discovery, providing significant acceleration
and cost reduction. As the most fundamental building block, molecular representation is …

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

As Large Language Models (LLMs) rapidly evolve, their influence in science is becoming
increasingly prominent. The emerging capabilities of LLMs in task generalization and free …

Abstract Machine learning, notably deep learning, has significantly propelled molecular
investigations within the biochemical sphere. Traditionally, modeling for such research has …

Capturing molecular knowledge with representation learning approaches holds significant
potential in vast scientific fields such as chemistry and life science. An effective and …

Language-molecule models have emerged as an exciting direction for molecular discovery
and understanding. However, training these models is challenging due to the scarcity of …