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An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response3h◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training3h◆Large language model and reinforcement learning based autonomous construction and progress updates3h◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring3h◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution3h◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing3h◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning3h◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System3h◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability3h◆Physical AI: Concepts, Techniques, and Challenges3h◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems3h◆A general-purpose System One decision model for clinical records3h◆EDMA: Entropy-Driven Multimodal Answering3h◆Learned Control Variates for Rare Grid-Outage Estimation at Electric Vehicle Charging Stations3h◆TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation3h◆When PTQ Calibration Helps or Hurts: Dose-Driven Collapse and Validation-Gated Abstention in Quantized Text Embedders3h◆Unified Sharp Bounds on Probabilities of Causation3h◆ProMemAgent: Long-Horizon Proactive Assistance with Context-Aware Prospective Memory from Sensory Perceptions3h◆Harness Self-Evolution for Long-Horizon Terminal Agents3h◆Ask to Distill: Learning to Synthesize Data for On-Policy Distillation3h◆An AI Security Agent for University ACMIS: Multi-Vector Threat Detection and Automated Response3h◆Navalia: Advancing Cowork Agents through Verifiable Task Synthesis and Long-Horizon Post-Training3h◆Large language model and reinforcement learning based autonomous construction and progress updates3h◆MedPAO-Assist: Edge-Deployable, Modality-Aware Agentic AI for Radiology Report Structuring3h◆DataPraxis: Scaling Analytics Tasks via Verified Workspace Evolution3h◆Industrial Agentic AI: LLM-Driven New-Generation Agents for Smart Manufacturing3h◆MAMath-Bench: Process-Aware and Robust Evaluation of Multimodal Multi-Agent Mathematical Reasoning3h◆LightCRS: Lightweight Multi-Domain Conversational Recommendation System3h◆When Planning Problems Become Hard for LLMs: Separating Structural Complexity from Semantic Interpretability3h◆Physical AI: Concepts, Techniques, and Challenges3h◆ReuF2F: Benchmarking Coding Agents on Formalized Undergraduate Research Problems3h◆A general-purpose System One decision model for clinical records3h◆EDMA: Entropy-Driven Multimodal Answering3h◆Learned Control Variates for Rare Grid-Outage Estimation at Electric Vehicle Charging Stations3h◆TEX: Test-Time Scaling Testing Agents via Execution-based Cross-Validation3h◆When PTQ Calibration Helps or Hurts: Dose-Driven Collapse and Validation-Gated Abstention in Quantized Text Embedders3h◆Unified Sharp Bounds on Probabilities of Causation3h◆ProMemAgent: Long-Horizon Proactive Assistance with Context-Aware Prospective Memory from Sensory Perceptions3h◆Harness Self-Evolution for Long-Horizon Terminal Agents3h◆Ask to Distill: Learning to Synthesize Data for On-Policy Distillation3h◆
News/Adobe Lightroom mobile can now open closed eyes in photos with a simple tap
theverge
PublishedOctober 20, 2026 at 1:06 PM

Adobe Lightroom mobile can now open closed eyes in photos with a simple tap

Adobe Lightroom mobile can now open closed eyes in photos with a simple tap
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Adobe announced yesterday that the mobile version of Lightroom, available for iOS, iPadOS, and Android, can now open closed eyes in photos using generative AI with just a single tap. When the app detects a person, or a group of people, have their eyes closed in a photo it will automatically present

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