Unmanned Aerial Vehicle (UAV), when equipped as communication relays, offer a flexible solution to extend Vehicle-to-Vehicle (V2V) communications beyond fixed infrastructure and Non-Line-of-Sight constraints. In this setting, the allocation of radio resources, across time, frequency and space through beamforming, is challenged by the mobility of Connected and Autonomous Vehicles (CAVs) and their temporal dependencies, as access opportunities depend on prior transmission outcomes such as queue backlog or failed attempts. This paper proposes a Radio Resource Assignment (RRA) framework […]

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arXiv:2601.00160v1 Announce Type: new Abstract: End-to-end automatic speech recognition has become the dominant paradigm in both academia and industry. To enhance recognition performance, the Weighted Finite-State Transducer (WFST) is widely adopted to integrate acoustic and language models through static graph composition, providing robust decoding and effective error correction. However, WFST decoding relies on a frame-by-frame autoregressive search over CTC posterior probabilities, which severely limits inference efficiency. Motivated by establishing a more principled compatibility between WFST decoding and CTC […]

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arXiv:2601.07985v1 Announce Type: new Abstract: The rapid proliferation of misinformation across online platforms underscores the urgent need for robust, up-to-date, explainable, and multilingual fact-checking resources. However, existing datasets are limited in scope, often lacking multimodal evidence, structured annotations, and detailed links between claims, evidence, and verdicts. This paper introduces a comprehensive data collection and processing pipeline that constructs multimodal fact-checking datasets in French and German languages by aggregating ClaimReview feeds, scraping full debunking articles, normalizing heterogeneous claim verdicts, […]

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The Rev. Dr. Richard Turnbull, long-time friend of the Acton Institute, sadly died on November 26, not long after being diagnosed with terminal cancer. Many friends, colleagues, and collaborators joined a Whatsapp group to pray for Richard and his family in his final weeks, and the affection and admiration that so many people had for him was clearly expressed over those weeks. Continue Reading…

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Executive Summary The era of the passive ‘recommendation engine’ is over. We are entering the age of Agentic  Commerce—where AI doesn’t just suggest, but acts with autonomy. Retail is entering a new  phase—Agentic Commerce—where artificial intelligence no longer merely suggests products,  but acts autonomously on behalf of consumers and enterprises. In this model, intelligent agents understand intent, evaluate constraints, reason across  alternatives, and execute end-to-end commerce workflows. For consumers, this means delegating  shopping decisions to trusted digital agents. […]

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Background: Automated visual field testing is fundamental in ophthalmology, but differences in stimulus scaling and luminance between devices hinder direct comparison of sensitivity values. Virtual reality (VR)–based perimetry has emerged as a portable alternative, yet its relationship with conventional perimetry requires clarification. Methods: This prospective cross-sectional study included 60 healthy participants stratified into younger (< 50 years) and older (≥ 50 years) groups. Differential light sensitivity was assessed in the right eye using Humphrey Automated Perimetry (HFA 30-2) […]

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These thirty-four powerful essays, based on Taoist and Buddhist thought, constitute a guide to what the author calls “non-volitional living”—the ancient understanding that our efforts to grasp our true nature are futile. Wei Wu Wei explains these venerable spiritual traditions in the context of modern experience, using wit and considerable precision to convey their profound insight into the very nature of existence.

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Introduction Disclaimer: This article is a cross post from Pytorch Medium Blog Post. One of the most exciting advancements, that has pushed the frontier of the Artificial Intelligence (AI) in recent years, is Deep Reinforcement Learning (DRL). DRL belongs to the family of machine learning algorithms. It assumes that intelligent machines can learn from their actions similar to the way humans learn from experience. Over the recent years we could witness some impressive real-world applications of DRL. The […]

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Continual learning (CL) for large language models (LLMs) aims to enable sequential knowledge acquisition without catastrophic forgetting. Memory replay methods are widely used for their practicality and effectiveness, but most rely on fixed, step-based heuristics that often misalign with the model’s actual learning progress, since identical training steps can result in varying degrees of parameter change. Motivated by recent findings that LLM forgetting mirrors the Ebbinghaus human forgetting curve, we propose FOREVER (FORgEtting curVe-inspired mEmory Replay), a novel […]

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