Link: http://arxiv.org/abs/2502.07312v1
PDF Link: http://arxiv.org/pdf/2502.07312v1
Summary: This report details Lumen Labs' novel approach to processing SocialNetworking Service (SNS) data.
We leverage knowledge distillation, specificallya simple distillation method inspired by DeepSeek-R1's CoT acquisition,combined with prompt hacking, to extract valuable training data from the Grokmodel.
This data is then used to fine-tune a Phi-3-mini model, augmented with amask-like mechanism specifically designed for handling the nuances of SNS data.
Our method demonstrates state-of-the-art (SOTA) performance on several SNS dataprocessing tasks, outperforming existing models like Grok, Phi-3, and GPT-4.
Weprovide a comprehensive analysis of our approach, including mathematicalformulations, engineering details, ablation studies, and comparativeevaluations.
Published on arXiv on: 2025-02-11T07:20:38Z