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

arXiv:2307.02185v3 Announce Type: replace-cross
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 …

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