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Counterfactual recoverability transforms how we approach error correction in on-policy distillation, leading to a staggering AUC of 1.000 compared to 0.392 with divergence alone.
CARGO-VL achieves a breakthrough in multimodal reliability by effectively managing conflicting evidence, leading to better decision-making in vision-language tasks.
Fourier decomposition of motion enables unprecedented accuracy in rendering dynamic scenes, tackling the limitations of traditional polynomial models.
Achieve robust SLAM in dynamic environments without semantic labels or depth sensors by disentangling scene dynamics with a generalizable motion model.
