[QA] Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale

from Arxiv Papers · host Igor Melnyk

The paper introduces PROX, a framework enabling small language models to refine data effectively, outperforming human-crafted methods and enhancing efficiency in LLM pre-training across various benchmarks. https://arxiv.org/abs//2409.17115 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers

Episode metadata supplied by the publisher feed · Published Sep 28, 2024

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[QA] Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale

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