JD Retail Technology
Mar 6, 2025 · Artificial Intelligence
Dynamic Margin Selection for Efficient Deep Learning and Low-Resource Large Model Training
Jia Xing’s research introduces Dynamic Margin Selection, a technique that repeatedly refreshes a core set of boundary‑close samples to train large language models efficiently on limited resources, achieving comparable loss to full‑data training, enabling six‑fold model compression, faster inference, and a proposed exponential scaling law for data‑efficient AI.
ICLRdynamic data selectionlarge language models
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