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Explained Simply</title>
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			<guid><![CDATA[https://provide.ai/12-ai-skills-that-will-decide-your-future-in-2026/]]></guid>
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			<guid><![CDATA[https://provide.ai/daily-ai-wrap-may-7-2026/]]></guid>
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			<title>Daily AI Wrap — May 7, 2026</title>
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			<title>Anthropic researchers detail “model spec midtraining”, which adds a stage between pretraining and fine-tuning to improve generalization from alignment training</title>
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			<guid><![CDATA[https://provide.ai/ai-powered-cmdb-why-configuration-management-databases-matter-more-than-ever/]]></guid>
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			<title>5 Best AI Tools Everyone Should Know in 2026</title>
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			<guid><![CDATA[https://provide.ai/how-cloud-cad-is-turning-engineering-workflows-into-organizational-memory/]]></guid>
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			<title>How Cloud CAD Is Turning Engineering Workflows Into Organizational Memory</title>
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			<guid><![CDATA[https://provide.ai/the-final-power-shift-why-humans-will-become-curators-in-the-agi-era/]]></guid>
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			<title>The Final Power Shift: Why Humans Will Become ‘Curators’ in the AGI Era</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:01:01 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/multi-model-ai-is-creating-a-routing-headache-for-enterprises/]]></guid>
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			<title>Multi-model AI is creating a routing headache for enterprises</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:57 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/proteo-r1-reasoning-foundation-models-for-de-novo-protein-design/]]></guid>
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			<title>Proteo-R1: Reasoning Foundation Models for De Novo Protein Design</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/example-based-object-detection/]]></guid>
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			<title>Example-Based Object Detection</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/opensearch-vl-an-open-recipe-for-frontier-multimodal-search-agents/]]></guid>
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			<title>OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/automated-formal-proofs-of-combinatorial-identities-via-wilf-zeilberger-guidance-and-llms/]]></guid>
			<link><![CDATA[https://provide.ai/automated-formal-proofs-of-combinatorial-identities-via-wilf-zeilberger-guidance-and-llms/]]></link>
			<title>Automated Formal Proofs of Combinatorial Identities via Wilf-Zeilberger Guidance and LLMs</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/malliavin-calculus-for-counterfactual-gradient-estimation-in-adaptive-inverse-reinforcement-learning-2/]]></guid>
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			<title>Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/noisycausal-a-benchmark-for-evaluating-causal-reasoning-under-structured-noise/]]></guid>
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			<title>NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/understanding-and-mitigating-bias-inheritance-in-llm-based-data-augmentation-on-downstream-tasks/]]></guid>
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			<title>Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/dynatab-dynamic-feature-ordering-as-neural-rewiring-for-high-dimensional-tabular-data/]]></guid>
			<link><![CDATA[https://provide.ai/dynatab-dynamic-feature-ordering-as-neural-rewiring-for-high-dimensional-tabular-data/]]></link>
			<title>DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/awaking-spatial-intelligence-in-unified-multimodal-understanding-and-generation/]]></guid>
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			<title>Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/learning-to-feel-the-future-dreamtacvla-for-contact-rich-manipulation/]]></guid>
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			<title>Learning to Feel the Future: DreamTacVLA for Contact-Rich Manipulation</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/mp-ismoe-mixed-precision-interactive-side-mixture-of-experts-for-efficient-transfer-learning/]]></guid>
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			<title>MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/sub-token-routing-in-lora-for-adaptation-and-query-aware-kv-compression-2/]]></guid>
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			<title>Sub-Token Routing in LoRA for Adaptation and Query-Aware KV Compression</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/full-chip-cmp-modelling-based-on-fully-convolutional-network-leveraging-white-light-interferometry/]]></guid>
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			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/mhpr-multidimensional-human-perception-and-reasoning-benchmark-for-large-vision-languate-models/]]></guid>
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			<title>MHPR: Multidimensional Human Perception and Reasoning Benchmark for Large Vision-Languate Models</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/dial-direct-iterative-adversarial-learning-for-realistic-multi-turn-dialogue-simulation/]]></guid>
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			<title>DIAL: Direct Iterative Adversarial Learning for Realistic Multi-Turn Dialogue Simulation</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/pamnet-cycle-aware-phase-amplitude-modulation-network-for-multivariate-time-series-forecasting/]]></guid>
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			<title>PAMNet: Cycle-aware Phase-Amplitude Modulation Network for Multivariate Time Series Forecasting</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/diffcap-bench-a-comprehensive-challenging-robust-benchmark-for-image-difference-captioning/]]></guid>
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			<title>DiffCap-Bench: A Comprehensive, Challenging, Robust Benchmark for Image Difference Captioning</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/lovif-2026-the-first-challenge-on-holistic-quality-assessment-for-4d-world-model-physcore/]]></guid>
			<link><![CDATA[https://provide.ai/lovif-2026-the-first-challenge-on-holistic-quality-assessment-for-4d-world-model-physcore/]]></link>
			<title>LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/structured-progressive-knowledge-activation-for-llm-driven-neural-architecture-search/]]></guid>
			<link><![CDATA[https://provide.ai/structured-progressive-knowledge-activation-for-llm-driven-neural-architecture-search/]]></link>
			<title>Structured Progressive Knowledge Activation for LLM-Driven Neural Architecture Search</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/geometry-aware-neural-optimizer-for-shape-optimization-and-inversion/]]></guid>
			<link><![CDATA[https://provide.ai/geometry-aware-neural-optimizer-for-shape-optimization-and-inversion/]]></link>
			<title>Geometry-Aware Neural Optimizer for Shape Optimization and Inversion</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/causalgaze-unveiling-hallucinations-via-counterfactual-graph-intervention-in-large-language-models-2/]]></guid>
			<link><![CDATA[https://provide.ai/causalgaze-unveiling-hallucinations-via-counterfactual-graph-intervention-in-large-language-models-2/]]></link>
			<title>CausalGaze: Unveiling Hallucinations via Counterfactual Graph Intervention in Large Language Models</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/telegraph-english-semantic-prompt-compression-via-structured-symbolic-rewriting/]]></guid>
			<link><![CDATA[https://provide.ai/telegraph-english-semantic-prompt-compression-via-structured-symbolic-rewriting/]]></link>
			<title>Telegraph English: Semantic Prompt Compression via Structured Symbolic Rewriting</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/scaling-laws-and-symmetry-evidence-from-neural-force-fields/]]></guid>
			<link><![CDATA[https://provide.ai/scaling-laws-and-symmetry-evidence-from-neural-force-fields/]]></link>
			<title>Scaling Laws and Symmetry, Evidence from Neural Force Fields</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/patre-a-full-stage-office-action-and-rebuttal-generation-benchmark-for-patent-examination/]]></guid>
			<link><![CDATA[https://provide.ai/patre-a-full-stage-office-action-and-rebuttal-generation-benchmark-for-patent-examination/]]></link>
			<title>PatRe: A Full-Stage Office Action and Rebuttal Generation Benchmark for Patent Examination</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/from-pixels-to-tokens-a-systematic-study-of-latent-action-supervision-for-vision-language-action-models/]]></guid>
			<link><![CDATA[https://provide.ai/from-pixels-to-tokens-a-systematic-study-of-latent-action-supervision-for-vision-language-action-models/]]></link>
			<title>From Pixels to Tokens: A Systematic Study of Latent Action Supervision for Vision-Language-Action Models</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/clamp-contrastive-learning-for-3d-multi-view-action-conditioned-robotic-manipulation-pretraining-2/]]></guid>
			<link><![CDATA[https://provide.ai/clamp-contrastive-learning-for-3d-multi-view-action-conditioned-robotic-manipulation-pretraining-2/]]></link>
			<title>CLAMP: Contrastive Learning for 3D Multi-View Action-Conditioned Robotic Manipulation Pretraining</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
		</item>
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			<guid><![CDATA[https://provide.ai/transformation-categorization-based-on-group-decomposition-theory-using-parameter-division/]]></guid>
			<link><![CDATA[https://provide.ai/transformation-categorization-based-on-group-decomposition-theory-using-parameter-division/]]></link>
			<title>Transformation Categorization Based on Group Decomposition Theory Using Parameter Division</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/the-power-of-order-fooling-llms-with-adversarial-table-permutations-2/]]></guid>
			<link><![CDATA[https://provide.ai/the-power-of-order-fooling-llms-with-adversarial-table-permutations-2/]]></link>
			<title>The Power of Order: Fooling LLMs with Adversarial Table Permutations</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/provable-imitation-learning-for-control-of-instability-in-partially-observed-vlasov-poisson-equations/]]></guid>
			<link><![CDATA[https://provide.ai/provable-imitation-learning-for-control-of-instability-in-partially-observed-vlasov-poisson-equations/]]></link>
			<title>Provable imitation learning for control of instability in partially-observed Vlasov&#8211;Poisson equations</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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			<guid><![CDATA[https://provide.ai/finstar-towards-financial-reasoning-with-time-series-reasoning-models/]]></guid>
			<link><![CDATA[https://provide.ai/finstar-towards-financial-reasoning-with-time-series-reasoning-models/]]></link>
			<title>FinSTaR: Towards Financial Reasoning with Time Series Reasoning Models</title>
			<pubDate><![CDATA[Thu, 07 May 2026 04:00:00 +0000]]></pubDate>
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