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CABLE boosts memory retrieval performance by focusing on complementary associations, achieving higher scores in scenarios with distributed evidence across sessions.
Static leaderboards can mislead deployment decisions, as a system with higher factuality may actually be less efficient when compute costs are factored in.
Logos present a unique challenge for concept unlearning, revealing that current methods often fail to erase them without compromising the integrity of the surrounding image.
Legato makes action-chunked VLA policies smoother and faster by learning a native continuation that eliminates the discontinuities introduced by chunking.
