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Surprisingly, a trie-guided decoding framework applied to smaller encoder-decoder models like T5 and BART can outperform much larger instruction-tuned models like LLaMA-3 and Phi-3 in in-document query auto-completion.
Forget struggling with ambiguous text descriptions – now you can automatically generate high-fidelity scientific architecture diagrams from natural language, thanks to a new dataset that rivals GPT-4o's diagramming abilities.
