arXiv:2601.20920v1 Announce Type: new Abstract: There are increasing indications that LLMs are not only used for producing scientific papers, but also as part of the peer review process. In this work, we provide the first comprehensive analysis of LLM use across the peer review pipeline, with particular attention to interaction effects: not just whether LLM-assisted papers or LLM-assisted reviews are different in isolation, but whether LLM-assisted reviews evaluate LLM-assisted papers differently. In particular, we analyze over 125,000 paper-review […]

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Multimodal-attributed graphs (MAGs) are a fundamental data structure for multimodal graph learning (MGL), enabling both graph-centric and modality-centric tasks. However, our empirical analysis reveals inherent topology quality limitations in real-world MAGs, including noisy interactions, missing connections, and task-agnostic relational structures. A single graph derived from generic relationships is therefore unlikely to be universally optimal for diverse downstream tasks. To address this challenge, we propose Task-aware Modality and Topology co-Evolution (TMTE), a novel MGL framework that jointly and iteratively […]

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Key Highlights: Countries in the Middle East are increasingly working to bolster plans for future innovations in advanced technology, AI, and other areas. One such example is the UAE. The country is partnering with some of the top tech giants from the U.S., like Microsoft and OpenAI, to make it more efficient in the AI sector. More recently, Microsoft announced $15.2 billion investment in the UAE to expand its AI footprint in the country. That’s not all; the […]

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Key Highlights: Meta has been under the European Commission’s radar for multiple reasons in the past. Now, it seems Facebook’s parent company is yet again in hot water in the EU. This time, the issue that the EC has flagged is related to access for third-party AI assistants inside WhatsApp. Late last year, the EU launched a probe into the matter. At the time, the EC said that its investigation would cover all regions in the EU except […]

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arXiv:2602.06837v1 Announce Type: cross Abstract: Hybrid modeling, the combination of machine learning models and scientific mathematical models, enables flexible and robust data-driven prediction with partial interpretability. However, effectively the scientific models may be ignored in prediction due to the flexibility of the machine learning model, making the idea of hybrid modeling pointless. Typically some regularization is applied to hybrid model learning to avoid such a failure case, but the formulation of the regularizer strongly depends on model architectures […]

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arXiv:2604.05113v1 Announce Type: new Abstract: Generative recommendation (GeneRec) has introduced a new paradigm that represents items as discrete semantic tokens and predicts items in a generative manner. Despite its strong performance across multiple recommendation tasks, existing GeneRec approaches still suffer from severe popularity bias and may even exacerbate it. In this work, we conduct a comprehensive empirical analysis to uncover the root causes of this phenomenon, yielding two core insights: 1) imbalanced tokenization inherits and can further amplify […]

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Following a boom in corporate wellness programs in the 2010s, data shows that companies are now significantly pulling back on workplace wellness offerings. Nike, for example, has scrapped its employees’ annual wellness week. At a time when cardiovascular complications, 80% of which are preventable through healthier lifestyles, are a leading cause of mortality in the U.S. and mental health conditions affect over a billion people globally, promoting healthy mental and physical habits in the workplace seems more relevant than ever. What’s more, according to research conducted by the McKinsey Health […]

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arXiv:2603.20227v1 Announce Type: new Abstract: Background: Telework has benefits for many people with disabilities. The pandemic may create new employment opportunities for people with disabilities by increasing employer acceptance of telework, but this crucially depends on the occupational structure. Objective: We compare people with and without disabilities in the expansion of telework as the pandemic began, and the evolution of telework during the pandemic. Methods: We use U.S. data from the American Community Survey from 2008 to 2020 […]

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arXiv:2510.24056v2 Announce Type: replace Abstract: Kernel Stein discrepancies (KSDs) are widely used for goodness-of-fit testing, but standard KSDs can be insensitive to higher-order dependence features such as tail dependence. We introduce the Copula-Stein Discrepancy (CSD), which defines a Stein operator directly on the copula density to target dependence geometry rather than the joint score. For Archimedean copulas, CSD admits a closed-form Stein kernel derived from the scalar generator. We prove that CSD metrizes weak convergence of copula distributions, […]

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