AttrScore

A recent focus of large language model (LLM) development, as exemplified by generative search engines, is to incorporate external references to generate and support its claims. However, evaluating the attribution, i.e., verifying whether the generated statement is indeed fully supported by the cited reference, remains an open problem.
We construct this dataset, which contains both training and test data for the evaluation of attribution. The training data are repurposed from related tasks, such as question answering, fact-checking, natural language inference, and summarization. The test data, cotains a set simulated from QA datasets and a set manually curated from a generative search engine, New Bing.