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Rhetorical framing can dramatically shift AI reviewers' scores, with evidence and novelty standing out as key influencers.
Self-evolving rubric rewards can dramatically enhance audio reasoning in models, outperforming traditional methods by adapting to the model's evolving capabilities.
Early hidden states of LLMs can predict steering success with surprising accuracy, enabling efficient steering without exhaustive rollouts.
LLMs can exhibit surprising "strategic realism" when analyzing an ongoing geopolitical conflict, but their reasoning falters in politically ambiguous situations, revealing critical domain-specific limitations.
