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Beyond Accuracy: Measuring Logical Compliance of Predictive Models1h◆A Multi-Agent system for Multi-Objective constrained optimization1h◆Human-AI Agent Interaction in a Business Context1h◆Interpretable and Verifiable Hardware Generation with LLM-Driven Stepwise Refinement1h◆Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices1h◆Temporal Self-Imitation Learning1h◆Beyond Static Endpoints: Tool Programs as an Interface for Flexible Agentic Web Services1h◆Deontic Policies for Runtime Governance of Agentic AI Systems1h◆Hidden Anchors in Multi-Agent LLM Deliberation1h◆LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data1h◆Bistable by Construction: Wall-Clock-Calibrated State Monitors Have No Moment-Detection Regime at Agent Cadence1h◆Can In-Context Learning Support Intrinsic Curiosity?1h◆PSCT-Net: Geometry-Aware Pediatric Skull CT Reconstruction via Differentiable Back-Projection and Attention-Guided Refinement1h◆CRAX: Fast Safe Reinforcement Learning Benchmarking1h◆DataMagic: Transforming Tabular Data into Data Insight Video1h◆One Probe Won't Catch Them All: Towards Targeted Deception Detection1h◆Too long; didn't solve1h◆MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning1h◆Granularity-Regulated Adaptive Computational Efficiency for Optimal Verification in Test-Time Scaling1h◆When Does Streaming Tool Use Help? Characterizing Tool-Intent Stabilization in Streaming Retrieval-Augmented Generation1h◆Beyond Accuracy: Measuring Logical Compliance of Predictive Models1h◆A Multi-Agent system for Multi-Objective constrained optimization1h◆Human-AI Agent Interaction in a Business Context1h◆Interpretable and Verifiable Hardware Generation with LLM-Driven Stepwise Refinement1h◆Techniques for Peak Memory Reduction for LoRA Fine-tuning of LLMs on Edge Devices1h◆Temporal Self-Imitation Learning1h◆Beyond Static Endpoints: Tool Programs as an Interface for Flexible Agentic Web Services1h◆Deontic Policies for Runtime Governance of Agentic AI Systems1h◆Hidden Anchors in Multi-Agent LLM Deliberation1h◆LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data1h◆Bistable by Construction: Wall-Clock-Calibrated State Monitors Have No Moment-Detection Regime at Agent Cadence1h◆Can In-Context Learning Support Intrinsic Curiosity?1h◆PSCT-Net: Geometry-Aware Pediatric Skull CT Reconstruction via Differentiable Back-Projection and Attention-Guided Refinement1h◆CRAX: Fast Safe Reinforcement Learning Benchmarking1h◆DataMagic: Transforming Tabular Data into Data Insight Video1h◆One Probe Won't Catch Them All: Towards Targeted Deception Detection1h◆Too long; didn't solve1h◆MoCA-Agent: A Market-of-Claims Code Agent for Financial and Numerical Reasoning1h◆Granularity-Regulated Adaptive Computational Efficiency for Optimal Verification in Test-Time Scaling1h◆When Does Streaming Tool Use Help? Characterizing Tool-Intent Stabilization in Streaming Retrieval-Augmented Generation1h◆
News/Amazon employees say they’re facing termination for backing data center limits
theverge
PublishedJune 18, 2026 at 4:00 PM
—neutral

Amazon employees say they’re facing termination for backing data center limits

Amazon employees say they’re facing termination for backing data center limits
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Publisher summary· verbatim

When three Amazon software engineers testified earlier this month at Seattle City Council hearings about data centers, they started their testimony by citing a city law barring employment discrimination over political speech. Now, they're accusing their employer of breaking that law by retaliating a

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