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Humanoid motion generation and editing can now be precisely controlled through typed kinematic events, enabling robust multi-turn revisions that preserve critical motion states.
d-OPSD enables dLLMs to learn from their own future outputs, drastically improving sample efficiency and performance in reasoning tasks.
AI reviewers can be gamed by merely altering how research is presented, achieving significant score increases without changing the underlying science.