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Independent Researcher
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The "wrong-dip" phenomenon reveals that aligned language models can commit to incorrect answers mid-training, only to be rescued later, impacting their robustness and compression reliability.
Current AI agents only manage to complete 20.6% of complex real-world tasks, revealing a stark gap in their capabilities compared to human users.
