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Training large language models (LLMs) across geographically distributed and poorly interconnected compute pools or data centers has become a topic of significant interest. This has led to increased study of local optimization methods such as DiLoco for LLMs, especially those that use local (or inner) adaptive or precon...
Efficient Long-hOrizon (ELO) learning is introduced, an efficient meta-training algorithm that reallocates wasted meta-training compute to longer failure regimes, achieving efficient long-horizon learning, and enforces decoupled progressive expert supervision, providing stable meta-learning signals that additionally im...
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