Artificial Intelligence (AI) benchmarks play a central role in measuring progress in model development and guiding deployment decisions. However, many benchmarks quickly become saturated, meaning that they can no longer differentiate between the best-performing models, diminishing their long-term value. In this study, we analyze benchmark saturation across 60 Large Language Model (LLM) benchmarks selected from technical reports by major model developers. To identify factors driving saturation, we characterize benchmarks along 14 properties spanning task design, data construction, and evaluation format. We test five hypotheses examining how each property contributes to saturation rates. Our analysis reveals that nearly half of the benchmarks exhibit saturation, with rates increasing as benchmarks age. Notably, hiding test data (i.e., public vs. private) shows no protective effect, while expert-curated benchmarks resist saturation better than crowdsourced ones. Our findings highlight which design choices extend benchmark longevity and inform strategies for more durable evaluation.
Long-horizon embodied planning is challenging because the world does not only change through an agent's actions: exogenous processes (e.g., water heating, dominoes cascading) unfold concurrently with the agent's actions. We propose a framework for abstract world models that jointly learns (i) symbolic state representations and (ii) causal processes for both endogenous actions and exogenous mechanisms. Each causal process models the time course of a stochastic cause-effect relation. We learn these world models from limited data via variational Bayesian inference combined with LLM proposals. Across five simulated tabletop robotics environments, the learned models enable fast planning that generalizes to held-out tasks with more objects and more complex goals, outperforming a range of baselines.
The complement of an arrangement of diagonal subspaces x_i_1=…=x_i_k in the real space is defined by a simplicial complex 𝒦 . In this paper, we prove that the complement of a diagonal subspace arrangement is homotopy equivalent to a subcomplex Perm(𝒦) of faces of the permutohedron. The product in the cohomology ring of the complement of a diagonal arrangement is then described via Saneblidze and Umble’s cellular approximation of the diagonal map in the permutohedron. We consider the projection from the permutohedron to the cube and prove that the Saneblidze–Umble diagonal is mapped to the diagonal constructed by Li Cai for describing the product in the cohomology of a real moment–angle complex.
This essay examines the automation development of China's Yangshan Port by benchmarking South Korea's Busan Port within the broader context of international maritime trade and port modernization. As global trade continues to expand, ports are increasingly required to improve efficiency, capacity, and technological integration in order to remain competitive.With the development of automation， many companies reduce investment in improving environmental protections and operational transparency. Therefore, in order to pursue long-term efficiency, a more comprehensive evaluating framework is needed. This study argues that port competitiveness is no longer determined solely by throughput or physical scale, but increasingly by the balance between Economic, Environmental, Social, and Governance (EESG) factors.Using a comparative EESG framework, this paper analyzes Yangshan Port and Busan Port across four dimensions: economic automation performance, environmental sustainability, social impact, and governance structure. The study highlights that Yangshan Port has a significant advantage in automation level and productive efficiency, while Busan port is more focused on environmental, social and governance factors. The findings suggest that although Yangshan Port demonstrates superior economic efficiency, Busan Port offers a more balanced EESG performance. Ultimately, we discover that there is a significant trade-off between efficiency and managing social and environmental externalities. Yangshan Port should refer to the Busan regulation and pollution solving model to strengthen environmental, social, governance(ESG) aspects.
This paper presents cryogenic-to-high-temperature characterization and compact modeling of p-type polysilicon resistors from 18.6 K to 473.15 K. Three resistor families (RPH, RP, and RPL) are characterized using four-terminal Kelvin structures across multiple geometries. RPH exhibits a strong, monotonic negative temperature coefficient of resistance (TCR) over the entire temperature range, whereas RP and RPL show geometry-dependent TCR sign changes and low-temperature saturation; several layouts achieve near-zero TCR over a wide temperature span. To capture these behaviors, a Matthiessen’s-rule-based double power law (DPL) temperature model is proposed, combining scattering contributions associated with grain boundaries and bulk/impurity effects. Compared with the conventional TC1/TC2 polynomial model, the proposed DPL model provides improved accuracy over the full temperature range and yields parameters that cluster by doping level and vary smoothly with geometry.
