#automated-optimization News & Analysis

2 articles tagged with #automated-optimization. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Jun 57/10

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Vortex: Efficient and Programmable Sparse Attention Serving for AI Agents

Vortex is a new system that simplifies the development and deployment of sparse attention algorithms for large language models, enabling researchers and AI agents to rapidly prototype and evaluate efficiency improvements. The platform demonstrates substantial real-world performance gains, with optimized algorithms achieving up to 3.46× higher throughput than full attention while maintaining accuracy, and successfully extending sparse attention to emerging model architectures.

🏢 Nvidia

AIBullisharXiv – CS AI · May 16/10

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From Context to Skills: Can Language Models Learn from Context Skillfully?

Researchers introduce Ctx2Skill, a self-evolving framework that automatically discovers and refines natural-language skills for language models to better learn from complex contexts without manual annotation or external feedback. The system uses a multi-agent loop with a Challenger, Reasoner, and Judge to autonomously generate, test, and improve skills, showing consistent improvements across context learning benchmarks.