arXiv:2507.01770v1 Announce Type: cross Abstract: This paper introduces a GPU-based complete search method to enclose the global minimum of a nonlinear function subject to simple bounds on the variables. Using interval analysis, coupled with the computational power and architecture of GPU, the method iteratively rules out the regions in the search domain where the global […]

[Submitted on 1 Jul 2025 (v1), last revised 2 Jul 2025 (this version, v2)] View a PDF of the paper titled Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess, by Dongyoon Hwang and 4 other authors View PDF HTML (experimental) Abstract:While reinforcement learning (RL) for large language models (LLMs) has shown

[Submitted on 24 Jun 2025 (v1), last revised 1 Jul 2025 (this version, v2)] View a PDF of the paper titled AirV2X: Unified Air-Ground Vehicle-to-Everything Collaboration, by Xiangbo Gao and 8 other authors View PDF HTML (experimental) Abstract:While multi-vehicular collaborative driving demonstrates clear advantages over single-vehicle autonomy, traditional infrastructure-based V2X systems remain constrained by substantial

arXiv:2507.01597v1 Announce Type: cross Abstract: Temporal Knowledge Graph (TKG) is an efficient method for describing the dynamic development of facts along a timeline. Most research on TKG reasoning (TKGR) focuses on modelling the repetition of global facts and designing patterns of local historical facts. However, they face two significant challenges: inadequate modeling of the event

TL;DR: Humans are developing new linguistic patterns to distinguish themselves from AI-generated content, and the rate of change will accelerate. How Dialects Form Dialects often emerge through geographical isolation (think Australian English vs British English). But there’s another powerful driver of dialect formation: the conscious or unconscious need to signal group affiliation and social identity.

Acknowledgments We thank Artem Dementyev, Alex Olwal, Mathieu Parvaix, Chiong Lai and Dimitri Kanevsky for their work on the SpeechCompass publication and research. Dmitrii Votintcev for ideas on prototypes and interaction designs. We are grateful to Pascal Getreuer, Richard Lyon, Alex Huang, Shao-Fu Shih, and Chet Gnegy for their help with algorithms. We also thank

A few days ago I wrote a shortform wondering if anyone had done a breakdown of the different state-level AI bills that had been proposed.  People seemed interested, and so I ended up doing the analysis and writing up my findings. This is the beginning of the piece, which is posted on my Substack: ~~~~

[Submitted on 28 Jun 2025 (v1), last revised 1 Jul 2025 (this version, v2)] View a PDF of the paper titled Hierarchical Decentralized Stochastic Control for Cyber-Physical Systems, by Kesav Kaza and 1 other authors View PDF HTML (experimental) Abstract:This paper presents a two-timescale hierarchical decentralized architecture for control of Cyber-Physical Systems. The architecture consists

arXiv:2507.00185v1 Announce Type: cross Abstract: Current artificial intelligence models for medical imaging are predominantly single modality and single disease. Attempts to create multimodal and multi-disease models have resulted in inconsistent clinical accuracy. Furthermore, training these models typically requires large, labour-intensive, well-labelled datasets. We developed MerMED-FM, a state-of-the-art multimodal, multi-specialty foundation model trained using self-supervised learning

[Submitted on 29 Nov 2024 (v1), last revised 30 Jun 2025 (this version, v3)] View a PDF of the paper titled A Graph-Based Classical and Quantum Approach to Deterministic L-System Inference, by Ali Lotfi and 2 other authors View PDF HTML (experimental) Abstract:L-systems can be made to model and create simulations of many biological processes,