Latest Insights on LLM Data Filtering and Training Methods
gabriberton · x · 2026-07-13
This is a summary of a podcast discussion on LLM data filtering:
- Data availability rebounds: Despite sites like Reddit restricting scraping, the volume of available text data has recovered to pre-LLM era levels.
- Data quality assessment & mid-training: Because single high-quality datasets like Wikipedia or GitHub are too small to pre-train a model from scratch, researchers first pre-train on noisy data. They then fine-tune separate LLMs on specific high-quality datasets for evaluation purposes, which are finally used for post-training. This intermediate fine-tuning step on specific datasets is now referred to as mid-training.
Related event: LLM Data Curation Insights: Data Rebound and Mid-training(6 posts)→
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