Scaling Up LLM Reviews for Google Ads Content Moderation

arXiv:2402.14590v1 Announce Type: cross
Abstract: Large language models (LLMs) are powerful tools for content moderation, but their inference costs and latency make them prohibitive for casual use on large datasets, such as the Google Ads repository. This study proposes a method for scaling up LLM reviews for content moderation in Google Ads. First, we use heuristics to select candidates via filtering and duplicate removal, and create clusters of ads for which we select one representative ad per cluster. We then …

abstract ads arxiv content moderation costs cs.cl cs.ir cs.lg datasets google google ads inference inference costs language language models large datasets large language large language models latency llm llms moderation reviews scaling scaling up study them tools type