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New Framework Reduces Visual Hallucinations in Multimodal AI Systems Without Retraining MAF Framework Dynamically Optimizes Prompting for Multimodal Sentiment Analysis Study on Pedestrian Attribute Recognition Identifies Sparsity Wall and Optimizes Edge Deployment AI Framework Targets 50% Water Loss in Jordan with LLM and Digital Twin Integration AnonShield: Scalable On-Premise Pseudonymization Cuts Vulnerability Data Processing from 92 Hours to Under 10 Minutes MoFore: A New Self-Supervised Framework Learns Video Representations by Forecasting Future Latent Embeddings Do LLMs Reliably Identify Correct Information Units in Aphasic Discourse? A New Study Evaluates Four Models AI Video Generation Method for Cardiac MRI Addresses Data Scarcity with Latent Motion Modeling SCAN Framework Helps CTOs Decide When to Use Generative AI for Task Allocation LLM-Encoded Knowledge Guides Federated Graph Recommendation to Improve Accuracy New Framework Reduces Visual Hallucinations in Multimodal AI Systems Without Retraining MAF Framework Dynamically Optimizes Prompting for Multimodal Sentiment Analysis Study on Pedestrian Attribute Recognition Identifies Sparsity Wall and Optimizes Edge Deployment AI Framework Targets 50% Water Loss in Jordan with LLM and Digital Twin Integration AnonShield: Scalable On-Premise Pseudonymization Cuts Vulnerability Data Processing from 92 Hours to Under 10 Minutes MoFore: A New Self-Supervised Framework Learns Video Representations by Forecasting Future Latent Embeddings Do LLMs Reliably Identify Correct Information Units in Aphasic Discourse? A New Study Evaluates Four Models AI Video Generation Method for Cardiac MRI Addresses Data Scarcity with Latent Motion Modeling SCAN Framework Helps CTOs Decide When to Use Generative AI for Task Allocation LLM-Encoded Knowledge Guides Federated Graph Recommendation to Improve Accuracy

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DH-V2: Geometry-Based Sampler Achieves 1,433x Compression for Edge Perception

Artificial Intelligence #computer vision#visual sampler

DH-V2: Geometry-Based Sampler Achieves 1,433x Compression for Edge Perception

Researchers present Double-Helix Vision (DH-V2), a geometry-based visual sampler that compresses 2D images into compact 1D signals using golden-ratio-inspired spiral trajectories. At 4K resolution, it achieves a 1,433x compression ratio while running in 0.52ms on CPU-only hardware, and includes a JSON-serializable Robotics API for bandwidth-constrained perception.

Jun 16, 2026 1 source

Philosophy Paper Argues Large Language Models Lack Agency for Moral Responsibility

Artificial Intelligence #large language models#intentionality

Philosophy Paper Argues Large Language Models Lack Agency for Moral Responsibility

A recent academic paper from arXiv argues that attributing agency or moral responsibility to large language models (LLMs) is misguided. The paper maintains that LLMs produce coherent outputs but are fully characterized by probabilistic input-output mappings, lacking intrinsic intentionality and self-attributed action. This challenges claims that LLMs can be moral agents, with direct relevance to how enterprises govern AI in decision-making.

Jun 16, 2026 1 source