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

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

We evaluate the effectiveness of pretrained and fine-tuned large language models (LLMs)
for predicting the synthesizability of inorganic compounds and the selection of precursors …

Large language models (LLMs) have gained widespread interest due to their ability to
process human language and perform tasks on which they have not been explicitly trained …

Chemistry plays a crucial role in many domains, such as drug discovery and material
science. While large language models (LLMs) such as GPT-4 exhibit remarkable …

In many scientific fields, large language models (LLMs) have revolutionized the way text and
other modalities of data (eg, molecules and proteins) are handled, achieving superior …

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 …

Large language models (LLM) have demonstrated emergent abilities in text generation,
question answering, and reasoning, facilitating various tasks and domains. Despite their …

In this perspective paper, we introduce the concept of Specialized Generalist Artificial
Intelligence (SGAI or simply SGI) as a crucial milestone toward Artificial General Intelligence …

We present SciRIFF (Scientific Resource for Instruction-Following and Finetuning), a dataset
of 137K instruction-following demonstrations for 54 tasks covering five essential scientific …