Search Results for author: Gopala Anumanchipali

Found 1 papers, 1 papers with code

LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement

1 code implementation22 Mar 2024 Nicholas Lee, Thanakul Wattanawong, Sehoon Kim, Karttikeya Mangalam, Sheng Shen, Gopala Anumanchipali, Michael W. Mahoney, Kurt Keutzer, Amir Gholami

LLM2LLM (1) fine-tunes a baseline student LLM on the initial seed data, (2) evaluates and extracts data points that the model gets wrong, and (3) uses a teacher LLM to generate synthetic data based on these incorrect data points, which are then added back into the training data.

Data Augmentation GSM8K +1

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