Citation: A Key to Building Responsible and Accountable Large Language Models

arXiv:2307.02185v3 Announce Type: replace
Abstract: Large Language Models (LLMs) bring transformative benefits alongside unique challenges, including intellectual property (IP) and ethical concerns. This position paper explores a novel angle to mitigate these risks, drawing parallels between LLMs and established web systems. We identify "citation" - the acknowledgement or reference to a source or evidence - as a crucial yet missing component in LLMs. Incorporating citation could enhance content transparency and verifiability, thereby confronting the IP and ethical issues in the …

abstract arxiv benefits building challenges concerns cs.ai cs.cl cs.cr ethical identify intellectual property key language language models large language large language models llms novel paper property reference responsible risks systems type web