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Negative token filtering enables stable single-rollout training, outperforming traditional group-based methods on agentic tasks while maintaining efficiency.
Overcoming perceptual uncertainty in vision-language navigation is now possible by explicitly modeling geometric, semantic, and appearance uncertainty with a novel Uncertainty-Aware Gaussian Map.
Ditch the slow "think-first-then-translate" paradigm: ReflectMT internalizes reflection, delivering faster and better machine translation in a single pass.
