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Robots using the SWAP model achieved record-breaking parkour feats, including a 2.13 m jump and a 1.63 m climb, demonstrating the power of symmetry in robotic learning.
Gaze behaviors learned through reinforcement alone can lead to unprecedented humanoid locomotion capabilities, including a record 1.2m gap traversal.
LLM agents are alarmingly susceptible to memory poisoning via conversational attacks, achieving 95% success rates even against agents with selective memory mechanisms.
LLMs can drastically improve entity resolution accuracy, but only if you intelligently integrate them into a global graph refinement process that minimizes query costs.
