Please refer to this table for full evaluations including Open LLM Leaderboard as well, which includes DEITA models with LLaMA base models and comparisons with other data selection approaches.

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Dec 3, 2025 · What is Deita? Deita is an open-source framework for automatic data selection in instruction tuning for Large Language Models (LLMs). The core innovation is achieving state-of-the …

We present DEITA(short for Data-Efficient Instruction Tuning for Alignment), a series of models fine-tuned from LLaMA and Mistral models using data samples automatically selected with our proposed …

Deita is an open-sourced project designed to facilitate Automatic Data Selection for instruction tuning in Large Language Models (LLMs). Deita Complexity Scorer is a tool for automatically annotating the …

DEITA (Data-Efficient Instruction Tuning for Alignment) studies an automatic data selection process by first quantifying the data quality based on complexity, quality and diversity.

DEITA (Data-Efficient Instruction Tuning for Alignment) studies an automatic data selection process by first quantifying the data quality based on complexity, quality and diversity.