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Gaoling School of Artificial Intelligence, Renmin University of China
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CausalMix reveals that dynamic data mixture optimization can significantly enhance LLM performance, adapting seamlessly to changing data distributions without the need for costly retraining.
A single multimodal model outperforms specialized approaches across 80 biological tasks, redefining the landscape of biological AI applications.
LLM datasets aren't independent islands: tracing their lineage reveals hidden redundancy, benchmark contamination, and opportunities for more diverse training data.
Forget simplistic synthetic data: ChartVerse generates complex charts and reliable reasoning data from scratch, enabling an 8B model to outperform its 30B teacher in chart reasoning.
