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Prompt-based agent memory inevitably saturates the context window, but alternating fast in-context skill distillation with slow parametric consolidation turns ephemeral interaction traces into durable model competence.
Water's density anomaly isn't just about mixed structures; it's a delicate balance of short-range order and intermediate-range collapse, revealed by a new machine-learned potential.
