What Makes a 3D Scene Editable? A Factorized Benchmark of Fidelity, Locality, Consistency, and Preservation
研究通过引入EditBench3D评估3D场景编辑的四个属性:保真度、局部性、一致性和非目标内容保留,使用多种编辑方法并揭示了各方法在不同维度上的表现差异。
研究通过引入EditBench3D评估3D场景编辑的四个属性:保真度、局部性、一致性和非目标内容保留,使用多种编辑方法并揭示了各方法在不同维度上的表现差异。
本文提出了一种名为AdaConRed的方法,通过将模糊预测集转化为明确分类来解决医学图像分类中过渡类别带来的不确定性问题。
本文通过结合机器学习代理模型与多目标优化策略,加速了黏弹性流体在微通道中电渗流动的设计优化过程,以提高能量转换效率和体积流量。
研究针对印地语法律判决中隐喻检测问题,通过构建HiLeMe语料库并使用mBERT及基于Transformer的架构,实现了对低资源语言中隐喻的有效识别。
This study addresses the problem of finite-state reduction in finitely-valued Heyting modal logics that preserves the exact truth values of formulas. Building on relational bi-topological duality, the work proposes a minimality-preserving reduction method by constructing an observational quotient structure via evaluation maps induced by modal subalgebras, ensuring that all formulas retain their precise truth values in the reduced model. The main contributions include proving that this observational quotient is isomorphic to a finite image within its bi-topological dual; constructing tree-shaped certificates of exact truth values for any formula and state, whose depth is bounded by modal depth and whose branching depends on the height of the truth-value algebra and the number of boxed subformulas; and, for the first time, providing bounded counterexample certificates that preserve exact falsity values in cases of truth-value failure.
研究通过引入EditBench3D评估3D场景编辑的四个属性:保真度、局部性、一致性和非目标内容保留,使用多种编辑方法并揭示了各方法在不同维度上的表现差异。
本文提出了一种名为AdaConRed的方法,通过将模糊预测集转化为明确分类来解决医学图像分类中过渡类别带来的不确定性问题。
本文通过结合机器学习代理模型与多目标优化策略,加速了黏弹性流体在微通道中电渗流动的设计优化过程,以提高能量转换效率和体积流量。
研究针对印地语法律判决中隐喻检测问题,通过构建HiLeMe语料库并使用mBERT及基于Transformer的架构,实现了对低资源语言中隐喻的有效识别。
This study addresses the problem of finite-state reduction in finitely-valued Heyting modal logics that preserves the exact truth values of formulas. Building on relational bi-topological duality, the work proposes a minimality-preserving reduction method by constructing an observational quotient structure via evaluation maps induced by modal subalgebras, ensuring that all formulas retain their precise truth values in the reduced model. The main contributions include proving that this observational quotient is isomorphic to a finite image within its bi-topological dual; constructing tree-shaped certificates of exact truth values for any formula and state, whose depth is bounded by modal depth and whose branching depends on the height of the truth-value algebra and the number of boxed subformulas; and, for the first time, providing bounded counterexample certificates that preserve exact falsity values in cases of truth-value failure.