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EFT enables LLMs to evolve solutions across diverse optimization tasks, achieving over 10% performance gains and state-of-the-art results in challenging mathematical problems.
ZPPO reveals that embedding teacher responses in prompts rather than gradients can dramatically boost the performance of small student models on challenging tasks.
TIDE uncovers hidden problems in user contexts, achieving substantial gains in task coverage and resolution that traditional methods miss.
Stop forcing all your data into one format – OmniRetrieval lets you query across text, tables, and graphs using their native structures, and it actually works better.
