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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 22

Domain-Adaptive Pretraining Enhances Water Treatment Semantic Representation for Large-Scale Structured Literature Mining

Water treatment research is expanding rapidly, but much of the knowledge acquired from this research remains scattered across unstructured literature. The field still lacks a dedicated language model that can efficiently capture water treatment-specific domain semantics for…

arXiv

Sep 22

Hyperbolic Restricted Boltzmann Machine Neural Quantum State

We construct the first type of non-Euclidean non-autoregressive neural quantum state (NQS) in the form of the hyperbolic Restricted Boltzmann Machine (HRBM), which is studied in the variational Monte-Carlo (VMC) setting of the Quantum Sherrington-Kirkpatrick (QSK) model whose…

arXiv

Sep 22

CQ4OE: A benchmark for assessing LLM-assisted ontology generation from competency questions

Ontology generation from Competency Questions (CQs) is a central yet labor-intensive phase of Ontology Engineering. While large language models (LLMs) offer promising automation capabilities, current evaluations remain fragmented. Task formulations are heterogeneous, gold…

arXiv

Sep 22

REVE: Efficient Hallucination Correction for Large Audio-Language Models via Reused Encoder States

Large audio-language models may mention acoustic events that are absent from the input. A separate audio event detector can verify these mentions, but doing so requires a second audio encoder and a separate forward pass. We propose Reused Encoder States for Verifying Events…

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