Can we soft prompt LLMs for graph learning tasks?

arXiv:2402.10359v1 Announce Type: new
Abstract: Graph plays an important role in representing complex relationships in real-world applications such as social networks, biological data and citation networks. In recent years, Large Language Models (LLMs) have achieved tremendous success in various domains, which makes applying LLMs to graphs particularly appealing. However, directly applying LLMs to graph modalities presents unique challenges due to the discrepancy and mismatch between the graph and text modalities. Hence, to further investigate LLMs' potential for comprehending graph information, …

abstract applications arxiv cs.cl cs.lg data domains graph graph learning graphs language language models large language large language models llms networks prompt relationships role social social networks success tasks type world