arXiv:2512.20723v1 Announce Type: new Abstract: The term artificial implies an inherent dichotomy from the natural or organic. However, AI, as we know it, is a product of organic ingenuity: designed, implemented, and iteratively improved by human cognition. The very principles that underpin AI systems, from neural networks to decision-making algorithms, are inspired by the organic […]
DiEC: Diffusion Embedded Clustering
arXiv:2512.20905v1 Announce Type: cross Abstract: Deep clustering hinges on learning representations that are inherently clusterable. However, using a single encoder to produce a fixed embedding ignores the representation trajectory formed by a pretrained diffusion model across network hierarchies and noise timesteps, where clusterability varies substantially. We propose DiEC (Diffusion Embedded Clustering), which performs unsupervised clustering […]
A Benchmark for Evaluating Outcome-Driven Constraint Violations in Autonomous AI Agents
arXiv:2512.20798v1 Announce Type: new Abstract: As autonomous AI agents are increasingly deployed in high-stakes environments, ensuring their safety and alignment with human values has become a paramount concern. Current safety benchmarks often focusing only on single-step decision-making, simulated environments for tasks with malicious intent, or evaluating adherence to explicit negative constraints. There is a lack […]
Consistent Opponent Modeling in Imperfect-Information Games
arXiv:2508.17671v5 Announce Type: replace-cross Abstract: The goal of agents in multi-agent environments is to maximize total reward against the opposing agents that are encountered. Following a game-theoretic solution concept, such as Nash equilibrium, may obtain a strong performance in some settings; however, such approaches fail to capitalize on historical and observed data from repeated interactions […]
Safety Alignment of LMs via Non-cooperative Games
arXiv:2512.20806v1 Announce Type: new Abstract: Ensuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rely on sequential adversarial training: generating adversarial prompts and fine-tuning LMs to defend against them. We introduce a different paradigm: framing safety alignment as a non-zero-sum game between an Attacker […]
Embodied AI-Enhanced IoMT Edge Computing: UAV Trajectory Optimization and Task Offloading with Mobility Prediction
arXiv:2512.20902v1 Announce Type: cross Abstract: Due to their inherent flexibility and autonomous operation, unmanned aerial vehicles (UAVs) have been widely used in Internet of Medical Things (IoMT) to provide real-time biomedical edge computing service for wireless body area network (WBAN) users. In this paper, considering the time-varying task criticality characteristics of diverse WBAN users and […]
MAR:Multi-Agent Reflexion Improves Reasoning Abilities in LLMs
arXiv:2512.20845v1 Announce Type: new Abstract: LLMs have shown the capacity to improve their performance on reasoning tasks through reflecting on their mistakes, and acting with these reflections in mind. However, continual reflections of the same LLM onto itself exhibit degeneration of thought, where the LLM continues to repeat the same errors again and again even […]
Improving Action Smoothness for a Cascaded Online Learning Flight Control System
arXiv:2507.04346v5 Announce Type: replace-cross Abstract: This paper aims to improve the action smoothness of a cascaded online learning flight control system. Although the cascaded structure is widely used in flight control design, its stability can be compromised by oscillatory control actions, which poses challenges for practical engineering applications. To address this issue, we introduce an […]
Using stationary information flows to prove kinetic uncertainty relations in biochemical control systems
arXiv:2512.20887v1 Announce Type: new Abstract: Many cellular components are present in such low numbers that individual stochastic production and degradation events lead to significant fluctuations in molecular abundances. Although feedback control can, in principle, suppress such low-copy-number fluctuations, general rules have emerged that suggest fundamental performance constraints on feedback control in biochemical systems. In particular, […]
PhononBench:A Large-Scale Phonon-Based Benchmark for Dynamical Stability in Crystal Generation
arXiv:2512.21227v1 Announce Type: cross Abstract: In this work, we introduce PhononBench, the first large-scale benchmark for dynamical stability in AI-generated crystals. Leveraging the recently developed MatterSim interatomic potential, which achieves DFT-level accuracy in phonon predictions across more than 10,000 materials, PhononBench enables efficient large-scale phonon calculations and dynamical-stability analysis for 108,843 crystal structures generated by […]