Large language models on graphs: A comprehensive survey
Large language models (LLMs), such as GPT4 and LLaMA, are creating significant
advancements in natural language processing, due to their strong text encoding/decoding …
advancements in natural language processing, due to their strong text encoding/decoding …
A survey of graph meets large language model: Progress and future directions
Graph plays a significant role in representing and analyzing complex relationships in real-
world applications such as citation networks, social networks, and biological data. Recently …
world applications such as citation networks, social networks, and biological data. Recently …
[HTML][HTML] Combined scaling for zero-shot transfer learning
Recent developments in multimodal training methodologies, including CLIP and ALIGN,
obviate the necessity for individual data labeling. These approaches utilize pairs of data and …
obviate the necessity for individual data labeling. These approaches utilize pairs of data and …
Protst: Multi-modality learning of protein sequences and biomedical texts
Current protein language models (PLMs) learn protein representations mainly based on
their sequences, thereby well capturing co-evolutionary information, but they are unable to …
their sequences, thereby well capturing co-evolutionary information, but they are unable to …
Shaping the water-harvesting behavior of metal–organic frameworks aided by fine-tuned GPT models
We construct a data set of metal–organic framework (MOF) linkers and employ a fine-tuned
GPT assistant to propose MOF linker designs by mutating and modifying the existing linker …
GPT assistant to propose MOF linker designs by mutating and modifying the existing linker …
Enhancing activity prediction models in drug discovery with the ability to understand human language
Activity and property prediction models are the central workhorses in drug discovery and
materials sciences, but currently, they have to be trained or fine-tuned for new tasks. Without …
materials sciences, but currently, they have to be trained or fine-tuned for new tasks. Without …
A survey on rag meeting llms: Towards retrieval-augmented large language models
As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …
Artificial intelligence for science in quantum, atomistic, and continuum systems
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …
Empowering molecule discovery for molecule-caption translation with large language models: A chatgpt perspective
Molecule discovery plays a crucial role in various scientific fields, advancing the design of
tailored materials and drugs, which contributes to the development of society and human …
tailored materials and drugs, which contributes to the development of society and human …
Git-mol: A multi-modal large language model for molecular science with graph, image, and text
Large language models have made significant strides in natural language processing,
enabling innovative applications in molecular science by processing textual representations …
enabling innovative applications in molecular science by processing textual representations …