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The University of Queensland
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LLM-derived user profiles can be powerfully leveraged for recommendation via a surprisingly simple distribution shaping approach, outperforming more complex fusion methods.
LLM agents can conquer complex Text-to-SQL by creating intermediate "agentic views" that break down queries and filter schemas, achieving state-of-the-art results on challenging benchmarks.
