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Department of Computer Science
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Optimal granularity in RAG benchmarks varies by dimension, with question complexity thriving on fine distinctions while other factors favor medium granularity.
You can accurately predict the NDCG of a 1B-parameter reranking model by only training models up to 400M parameters, unlocking massive compute savings.
