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US threatens sanctions against Chinese AI models over IP theft52m◆Google launches a cheaper alternative to large AI security models like Mythos1h◆Music streamer Deezer says more than 50% of daily uploads are AI-generated3h◆Halliday’s latest smart glasses feature a much-improved display3h◆America needs to stop getting shocked by Chinese AI5h◆Advancing next-gen AI with materials science innovation5h◆Gritt exits stealth with $32 million for robots to build solar plants — then, everything else6h◆Capacity and Redundancy Trade-offs in Multi-Task Learning12h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation12h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making12h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection12h◆Supervised Reward Inference12h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization12h◆Is Progressive Disclosure All You Need for Long-Context Agents?12h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability12h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification12h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration12h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI12h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models12h◆AI-Augmented Human Resource Management? Insights from German companies12h◆US threatens sanctions against Chinese AI models over IP theft52m◆Google launches a cheaper alternative to large AI security models like Mythos1h◆Music streamer Deezer says more than 50% of daily uploads are AI-generated3h◆Halliday’s latest smart glasses feature a much-improved display3h◆America needs to stop getting shocked by Chinese AI5h◆Advancing next-gen AI with materials science innovation5h◆Gritt exits stealth with $32 million for robots to build solar plants — then, everything else6h◆Capacity and Redundancy Trade-offs in Multi-Task Learning12h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation12h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making12h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection12h◆Supervised Reward Inference12h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization12h◆Is Progressive Disclosure All You Need for Long-Context Agents?12h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability12h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification12h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration12h◆Scientific reasoning does not reliably translate into scientific forecasting in frontier AI12h◆Language Triggers Hijack Language Circuits: A Mechanistic Analysis of Backdoor Behaviors in Large Language Models12h◆AI-Augmented Human Resource Management? Insights from German companies12h◆
News/model/reka-edge-2603

reka-edge-2603 news

2 articles mentioning reka-edge-2603

arxivJun 15

EurekAgent: Agent Environment Engineering is All You Need For Autonomous Scientific Discovery

arXiv:2606.13662v2 Announce Type: replace Abstract: LLM-based agents have shown increasing potential in automating scientific discovery. Given an optimizable metric and an execution environment, they can propose, validate, and iterate scientific solutions, and have produced results that outperform h

arxivMay 29

Eureka: Intelligent Feature Engineering for Enterprise AI Cloud Resource Demand Prediction

arXiv:2605.25297v2 Announce Type: replace-cross Abstract: Effective features are crucial for predictive model performance, but creating them often requires domain expertise, limiting scalability across applications. We define feature engineering as an agentic code generation problem: features are no

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