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Pulse · computing.co.uk

computing.co.uk · Nov 5

Revolut turns to self-hosted AI to cut coding costs tenfold over Claude

Pulse · wazzup.ph

wazzup.ph · Nov 5

Tencent Cloud Expands Global Growth and Enterprise AI

Overseas customer base doubles amid triple-digit growth in demand for AI products and services. Tencent previews upcoming Hy4 model releases and expands its enterprise AI portfolio. Tencent has unveiled the enterprise capabilities of its AI office productivity agent, WorkBuddy, while offering a preview of its upcoming Hy4 and Hy4 Flash models at the 2026 Tencent […]

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arXiv

Nov 4

From Pixels to Actions - Towards Native Vision-Language-Action Policies

Vision-language-action models are typically built on a simple premise: perception is first compressed by visual encoders, and action reasoning begins only afterwards. Yet manipulation often hinges on precisely the visual signals most vulnerable to this abstraction, e.g., local geometry, boundaries, depth, and subtle state changes. This raises a fundamental question: should action policies inherit a fixed visual endpoint, or directly access evolving visual computation? We introduce NEO-VLA, a structurally encoder-free vision-language-action framework. Images are tokenized by lightweight patch convolutional layers and evolve jointly with language throughout the backbone, allowing a flow-matching action expert to draw from instruction-conditioned visual representations at different depths. This simple change reveals a consistent pattern. Native architectures outperform encoder-based counterparts under controlled comparisons; full fine-tuning reduces but does not erase the gap, and additional scale alone cannot recover it. More strikingly, layer-wise probing shows that the action-critical signals often peak well before the final visual representation. Across diverse manipulation…

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arXiv

Sep 23

Leakage-Safe Machine Learning for Hydrogen Embrittlement Detection in 316L Stainless Steel: A Region-Held-Out Evaluation of Texture and Deep Features in SEM Micrographs

Scanning electron microscopy (SEM) is routinely used to characterize the microstructural changes caused by hydrogen embrittlement (HE) in structural steels. Machine learning can automate this characterization, but models are often evaluated using image-level splits. When…

arXiv

Sep 23

SynSeq: End-to-End SYNTAX Score Prediction from Coronary Angiography Videos

The SYNTAX score is an established tool for assessing coronary artery disease and guiding revascularization treatment decisions. However, its manual estimation from coronary angiography videos by clinical experts is time-consuming and subject to inter-reader variability. While…

arXiv

Sep 23

Consequential Behaviour and Representational Fairness in the Validation of Synthetic Research

Researchers in industry and academia use synthetic survey respondents powered by large language models as substitutes for human samples. These synthetic populations require validation against real-world data, so researchers often address them using ad hoc comparisons with human…

arXiv

Sep 23

When Explanations Cannot Be Read: Measuring and Correcting SHAP and LIME Rendering for Right-to-Left Languages

Post hoc explanation methods such as SHAP and LIME are widely used to interpret text classifiers, but their visualizations are mainly designed for left-to-right languages. When applied to right-to-left (RTL) languages such as Urdu, Arabic, Persian, and Hebrew, the attribution…

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