FIB (Factual Inconsistency Benchmark)
Introduced by Tam et al. in Evaluating the Factual Consistency of Large Language Models Through News Summarization
Factual Inconsistency Benchmark (FIB) is a benchmark that focuses on the task of summarization. Specifically, the benchmark involves comparing the scores an LLM assigns to a factually consistent versus a factual inconsistent summary for an input news article. For factually consistent summaries, human-written reference summaries are used to manually verify as factually consistent.
Source: Evaluating the Factual Consistency of Large Language Models Through SummarizationPapers
| Paper | Code | Results | Date | Stars |
|---|
Dataset Loaders
No data loaders found. You can
submit your data loader here.
No data loaders found. You can
submit your data loader here.
