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FlavourBench reveals that automated culinary evaluations can provide a more reliable ranking of language models than traditional human or model-based assessments.
Multi-model systems are constrained by a co-failure ceiling, revealing that simply adding models does not guarantee improved accuracy.
AURA-Mem achieves superior memory efficiency for robotic policies by intelligently controlling write operations, outperforming traditional KV-caches in both accuracy and resource usage.
Forget word embeddings, now you can embed *ingredients* with Epicure, a new family of models that captures both recipe context and chemical properties.
