Data Optimization for LLMs: A Survey

arXiv cs.AIOctober 27, 2026en

arXiv cs.AI

AI Global Wire

arXiv:2610.33405v1 Announce Type: new Abstract: Large language models (LLMs) have attracted great attention in both academic and industrial communities in recent years. Numerous survey studies have covered various aspects of LLMs, such as learning strategies, applications, alignment, explainability, and evaluation. However, little headway has been made in reviewing data-related aspects for LLMs, despite data being recognized as a key factor contributing to the emergence of the LLMs era. A wide range of data optimization algorithms and techniques are employed in LLMs' training and application processes. These techniques often originate from diverse deep learning domains, with their theoretica

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