arXiv:2603.11601v2 Announce Type: replace
Abstract: Vision-Language Models (VLMs) excel at describing visual scenes, yet struggle to translate perception into precise, grounded actions. We investigate whether providing VLMs with both the visual frame …
arXiv:2603.25898v1 Announce Type: cross
Abstract: LLM-assisted modeling holds the potential to rapidly build executable Digital Twins of complex systems from only coarse descriptions and sensor data. However, resilience to LLM hallucination, human ove…
arXiv:2511.04235v4 Announce Type: replace
Abstract: Constructing a consistent shared spatial memory is a critical challenge in multi-agent systems, where partial observability and limited bandwidth often lead to catastrophic failures in coordination. …
arXiv:2603.25880v1 Announce Type: cross
Abstract: Protein structural ensembles from NMR spectroscopy capture biologically important conformational heterogeneity, but it remains difficult to determine whether observed variation reflects coordinated mot…
arXiv:2501.05765v4 Announce Type: replace
Abstract: Ensuring ethical behavior in Artificial Intelligence (AI) systems amidst their increasing ubiquity and influence is a major concern the world over. The use of formal methods in AI ethics is a possibl…
arXiv:2305.09840v4 Announce Type: replace
Abstract: Balancing exploration and exploitation has been an important problem in both game tree search and automated planning. However, while the problem has been extensively analyzed within the Multi-Armed B…
arXiv:2603.26592v1 Announce Type: cross
Abstract: Reliable machine-learning models in biomedical settings depend on accurate labels, yet annotating biomedical time-series data remains challenging. Algorithmic sample selection may support annotation, b…
arXiv:2603.25861v1 Announce Type: cross
Abstract: Activation-based probes have emerged as a promising approach for detecting deceptively aligned AI systems by identifying internal conflict between true and stated goals. We identify a fundamental blind…
arXiv:2603.23582v2 Announce Type: replace-cross
Abstract: Accurate sleep staging is essential for diagnosing OSA and hypopnea in stroke patients. Although PSG is reliable, it is costly, labor-intensive, and manually scored. While deep learning enables…
arXiv:2603.25839v1 Announce Type: cross
Abstract: Deep neural networks exhibit a simplicity bias, a well-documented tendency to favor simple functions over complex ones. In this work, we cast new light on this phenomenon through the lens of the Minimu…