arXiv:2508.08672v2 Announce Type: replace-cross Abstract: Generative AI is being massively deployed in digital services, at a scale that will result in significant environmental harm. We document how tech companies are transforming established user interfaces to impose AI use and show…
arXiv:2509.10423v1 Announce Type: new Abstract: Reinforcement Learning (RL) agents deployed in real-world environments face degradation from sensor faults, actuator wear, and environmental shifts, yet lack intrinsic mechanisms to detect and diagnose these failures. We present an information-theoretic framework that reveals…
arXiv:2509.02853v3 Announce Type: replace-cross Abstract: Despite extensive investment in artificial intelligence, 95% of enterprises report no measurable profit impact from AI deployments (MIT, 2025). In this theoretical paper, we argue that this gap reflects paradigmatic lock-in that channels AI into…
arXiv:2509.08919v1 Announce Type: cross Abstract: The rapid adoption of generative AI-powered search engines like ChatGPT, Perplexity, and Gemini is fundamentally reshaping information retrieval, moving from traditional ranked lists to synthesized, citation-backed answers. This shift challenges established Search Engine Optimization (SEO)…
arXiv:2509.09775v1 Announce Type: new Abstract: This paper presents boldsea, Boldachev’s semantic-event approach — an architecture for modeling complex dynamic systems using executable ontologies — semantic models that act as dynamic structures, directly controlling process execution. We demonstrate that integrating event…
arXiv:2509.09177v1 Announce Type: cross Abstract: We propose FSPO (Fair Sequence Policy Optimization), a sequence-level reinforcement learning method for LLMs that enforces length-fair clipping directly in the importance-sampling (IS) weight space. We revisit sequence-level RL methods and identify a mismatch when…
arXiv:2509.10057v1 Announce Type: cross Abstract: We address the problem of automatic synchronisation of the spintronic oscillator (STO) by means of reinforcement learning (RL). A numerical solution of the macrospin Landau-Lifschitz-Gilbert-Slonczewski equation is used to simulate the STO and we train…
arXiv:2509.09470v1 Announce Type: cross Abstract: Keeping pace with the rapid growth of academia literature presents a significant challenge for researchers, funding bodies, and academic societies. To address the time-consuming manual effort required for scholarly discovery, we present a novel, fully…
arXiv:2509.10078v1 Announce Type: cross Abstract: Researchers have applied established psychometric questionnaires (e.g., BFI, PVQ) to measure the personality traits and values reflected in the responses of Large Language Models (LLMs). However, concerns have been raised about applying these human-designed questionnaires…
arXiv:2509.09681v1 Announce Type: cross Abstract: This paper presents the db3 team’s winning solution for the Meta CRAG-MM Challenge 2025 at KDD Cup’25. Addressing the challenge’s unique multi-modal, multi-turn question answering benchmark (CRAG-MM), we developed a comprehensive framework that integrates tailored…
