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Xiamen University
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Current VLM unlearning methods mostly just hide the data you want gone, and can be easily bypassed with clever prompting or retraining.
Achieve efficient and positionally consistent simultaneous machine translation with LLMs, regardless of the positional encoding method, using a surprisingly simple explicit position allocation strategy.
Forget brittle multi-policy execution and manual resets: RoboClaw's "Entangled Action Pairs" let robots self-correct and learn continuously, slashing human intervention by over 50% while boosting task success.
