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Fondazione Bruno Kessler
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Simple prompting methods consistently outperform advanced dense supervision techniques, challenging the current assumptions in LLM training strategies.
Unlabeled data can be transformed into powerful training examples, boosting classification performance by nearly 20 points without the need for costly annotations.
