Datasets for Large Language Models: A Comprehensive Survey (arxiv.org)

A new comprehensive survey has been released, focusing on the datasets that form the backbone of Large Language Models (LLMs). This research highlights the importance of these datasets as foundational elements that enhance LLM development and addresses a notable gap in the existing literature regarding their categorization, status, and future trends. The survey systematically categorizes 444 datasets across five key areas: pre-training corpora, instruction fine-tuning datasets, preference datasets, evaluation datasets, and traditional NLP datasets. Notably, the total data size surveyed exceeds 774.5 TB for pre-training data alone, demonstrating the vast scale of resources fueling advancements in LLM technology. This work is significant for the AI/ML community as it provides a crucial reference point for researchers, delineating the current landscape of LLM datasets and spotlighting the challenges that need addressing. By offering a detailed overview of existing datasets, the survey paves the way for more targeted and effective research efforts in language modeling. Researchers can leverage the insights gained to identify gaps and opportunities for innovation within the field, ultimately contributing to the evolution of LLM capabilities.