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University of Massachusetts Amherst
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Learning dynamic representation programs can boost retrieval performance by over 30% compared to traditional static methods.
Forget Claude and GPT: KARL, a reinforcement-learning-trained enterprise search agent, achieves Pareto-optimal performance on a diverse suite of search tasks, even outperforming closed models with sufficient compute.
