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A focused stream of recent stories from the sources curated for this community. Latest: Institution-Specific LLM Prompting Recovers PHI That De-identification Systems and Their Gold Standards Both Miss, Cross-Model Memory Transfer via Target-Side Reader Adaptation, and Margin-Regularized Structured Semantic Alignment for Brain-Language Correspondence. Page 145.
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Abstract page for arXiv paper 2608.17051: Institution-Specific LLM Prompting Recovers PHI That De-identification Systems and Their Gold Standards Both Miss
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Abstract page for arXiv paper 2608.17050: Cross-Model Memory Transfer via Target-Side Reader Adaptation
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Abstract page for arXiv paper 2608.16975: Margin-Regularized Structured Semantic Alignment for Brain-Language Correspondence
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Abstract page for arXiv paper 2608.17124: A decodability criterion predicts when hidden-state selection beats majority voting in large language models
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Abstract page for arXiv paper 2608.17071: KernelArc: A Multi-Agent Framework for GPU Kernel Optimization
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Abstract page for arXiv paper 2608.17053: Memory Is Communication: The Frontier Between Remembering and Signaling
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Abstract page for arXiv paper 2608.17007: SkillEffect: Checked Lowering for Memory-Bounded Agent Tools
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Abstract page for arXiv paper 2608.16977: The Problem Is the Problem: Towards Scalable Mathematical Discovery
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Abstract page for arXiv paper 2608.16956: The Price of Thinking: Reasoning Effort as a Model-Specific API Contract
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Abstract page for arXiv paper 2608.16891: Runtime Governance for Agentic AI: Action-Boundary Control with Trusted Provenance and Fail-Closed Execution
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Abstract page for arXiv paper 2608.16890: GxP-Agent: Process-DAG Topology for Reliable Clinical Trial Programming with LLM Agents
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How Python does AI: agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end. - Release v2.32.0 (2026-08-18) · pydantic/pydantic-ai
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