Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration

arXiv:2310.00280v2 Announce Type: replace-cross
Abstract: Large Language Models (LLMs) are evolving at an unprecedented pace and have exhibited considerable capability in the realm of natural language processing (NLP) with world knowledge. Benefiting from ultra-large-scale training corpora, a single LLM can manage typical NLP tasks competently. However, its performance in executing reasoning tasks is still confined by the limitations of its internal representations. To push this boundary further, we introduce Corex in this paper, a suite of novel general-purpose strategies that …

abstract arxiv capability collaboration cs.ai cs.cl however knowledge language language models language processing large language large language models llm llms natural natural language natural language processing nlp performance processing realm reasoning scale tasks through training type world