Amidst therecent strides inevaluating LargeLanguage Models forCode (Code LLMs), existing benchmarks havemainly focused onthefunctional correctness of generated code, neglecting the importance of their computational efficiency.

Deepneural Arguably (open-sourced) evaluate time-consuming significance ership security ofpoison-only explore behaviors andpro watermark tousethe tion.

This algorithm approximates the integral involvedinthe definition ofthe Projected Jacobian with a standard Riemann sum. Note that the definition ofX0 implies that the baseline vectorx0 is broadcasted alongthefirstdimension ofthematrix.

DePT induces a cone-shaped spatial-temporal attention prior,which injects theinformation propagation and aggregation principles and enables a global view. With physical constraint inductive bias baked into its design, our DePT is ready to plug and play for a broad class of multi-agent systems. The experimental results on one of the most challenging CPS - network-scale traffic signal control system in the open world - show that our model outperformed the state-of-the-art expert methods on synthetic and real-world datasets.

Furthermore, we develop a method to eliminate bias in cases where blindly assuming IID is expected to yield a significantly biased estimate.