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Reduce your MoE LLM's memory bottleneck by up to 49% with a simple router fine-tuning trick that encourages experts to be reused.
Meta's new hierarchical indexing method lets you deploy massive recommendation models without sacrificing speed or accuracy, and it turns out the index itself highlights a high-quality subset of data perfect for test-time training.
VLMs still struggle to generate code for complex, multi-panel charts from real-world data, despite excelling on simpler benchmarks.
