All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining

arXiv:2402.09834v1 Announce Type: new
Abstract: Large Language Models (LLMs) have revolutionized the fields of computer vision (CV) and natural language processing (NLP). One of the most notable advancements of LLMs is that a single model is trained on vast and diverse datasets spanning multiple domains -- a paradigm we term `All in One'. This methodology empowers LLMs with super generalization capabilities, facilitating an encompassing comprehension of varied data distributions. Leveraging these capabilities, a single LLM demonstrates remarkable versatility across a …

abstract and natural language processing arxiv computer computer vision cs.lg datasets diverse domain fields graph language language models language processing large language large language models llms multiple natural natural language natural language processing nlp pretraining processing simple type vast vision