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Found 2 papers, 1 papers with code
RAGGED: Towards Informed Design of Retrieval Augmented Generation Systems
RAGGED offers further insights into LMs' context utilization habits, where we find that encoder-decoder models rely more on contexts and are thus more sensitive to retrieval quality, while decoder-only models tend to rely on knowledge memorized during training.
Goodhart's Law Applies to NLP's Explanation Benchmarks
First, we show that we can inflate a model's comprehensiveness and sufficiency scores dramatically without altering its predictions or explanations on in-distribution test inputs.
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