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Recursive self-improvement in LLMs can lead to unprecedented performance, with Meta^n surpassing all prior agents on challenging benchmarks by leveraging fixed meta-operations.
LALMs are falling short in paralinguistic evaluations, missing the mark by 32 percentage points compared to human judges.
VLMs falter in strategic reasoning, with performance dropping sharply in complex RTS scenarios that require tight coordination and long-horizon planning.
