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Achieving a Relational Delivery Score of 66.6% reveals that even advanced models struggle with the complexities of merging interacting pull requests safely.
Instruction leakage can lead to misleadingly high accuracy in spatial relation tasks, revealing a critical flaw in goal-conditioned models that could misguide future research.
A novel zero-parameter gating mechanism boosts UAV video segmentation performance by over 4% while maintaining temporal stability.
LLM-generated test suites are shockingly bad at catching even simple code mutations, with even the best models failing to detect over 60% of them.
By strategically dropping "anchor" Gaussians and their neighbors, DropAnSH-GS overcomes the limitations of naive dropout in 3D Gaussian Splatting, leading to more robust and globally informed scene representations under sparse-view conditions.
