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Griffith University
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FLEXRec shows that compact LLMs can achieve state-of-the-art recommendation accuracy without the computational burden of larger models.
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.
FusionSQL lets you evaluate Text2SQL models on new databases without any labels, saving time and money while ensuring quality.
