SpecUBench is a benchmark for measuring the LLM-specific utility of retrieved
passages in retrieval-augmented generation (RAG). Instead of assuming that a
"relevant" passage is equally useful to every reader, UtilityBench labels how useful
each retrieved passage is for a specific LLM — i.e., how much the passage actually
helps that model produce the correct answer.
The benchmark is built on six widely-used open-domain QA / retrieval… See the full description on the dataset page:
https://huggingface.co/datasets/Trustworthy-Information-Access/SpecUBench.
