arXiv:2511.22325v1 Announce Type: new Abstract: Urban economic vitality is a crucial indicator of a city’s long-term growth potential, comprising key metrics such as the annual number of new companies and the population employed. However, modeling urban economic vitality remains challenging.…
arXiv:2511.23442v1 Announce Type: cross Abstract: Offline reinforcement learning (RL) enables agents to learn optimal policies from pre-collected datasets. However, datasets containing suboptimal and fragmented trajectories present challenges for reward propagation, resulting in inaccurate value estimation and degraded policy performance. While…
arXiv:2511.22376v1 Announce Type: new Abstract: Argumentation frameworks, consisting of arguments and an attack relation representing conflicts, are fundamental for formally studying reasoning under conflicting information. We use methods from mathematical logic, specifically computability and set theory, to analyze the grounded…
arXiv:2508.02583v4 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated strong performance across a wide range of tasks, yet they still struggle with complex mathematical reasoning, a challenge fundamentally rooted in deep structural dependencies. To address this challenge, we…
arXiv:2511.22386v1 Announce Type: new Abstract: The principle of minimal change in belief revision theory requires that, when accepting new information, one keeps one’s belief state as close to the initial belief state as possible. This is precisely what the method…
arXiv:2205.12186v3 Announce Type: replace-cross Abstract: Continual learning aims to sequentially learn new tasks without forgetting previous tasks’ knowledge (catastrophic forgetting). One factor that can cause forgetting is the interference between the gradients on losses from different tasks. When the gradients…
arXiv:2511.22448v1 Announce Type: new Abstract: Business Process Model and Notation (BPMN) is a widely adopted standard for representing complex business workflows. While BPMN diagrams are often exchanged as visual images, existing methods primarily rely on XML representations for computational analysis.…
arXiv:2503.20138v3 Announce Type: replace-cross Abstract: Current network training paradigms primarily focus on either centralized or decentralized data regimes. However, in practice, data availability often exhibits a hybrid nature, where both regimes coexist. This hybrid setting presents new opportunities for model…
arXiv:2511.22536v1 Announce Type: new Abstract: Originating in psychology, $textit{Theory of Mind}$ (ToM) has attracted significant attention across multiple research communities, especially logic, economics, and robotics. Most psychological work does not aim at formalizing those central concepts, namely $textit{goals}$, $textit{intentions}$, and…
arXiv:2506.03195v2 Announce Type: replace-cross Abstract: Despite Multimodal Large Language Models (MLLMs) showing promising results on general zero-shot image classification tasks, fine-grained image classification remains challenging. It demands precise attention to subtle visual details to distinguish between visually similar subcategories–details that…
