#ml-systems News & Analysis

3 articles tagged with #ml-systems. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · Jun 256/10

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ASAP: Agent-System Co-Design for Wall-Clock-Centered Auto HPO Research for ML Experiments

Researchers introduce ASAP, an agent-system co-design that leverages LLMs to coordinate multiple hyperparameter optimization tools while reducing wall-clock execution time through architectural innovations like KV-cache reuse and speculation parallelism. The approach addresses fundamental limitations in current LLM-based HPO methods by treating the language model as an orchestrator rather than a replacement tool, demonstrating consistent performance improvements across diverse ML tasks.

AINeutralarXiv – CS AI · Jun 96/10

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Training-Inference Kernel Contracts: Bounding Divergence in Post-Training and Deployment

Researchers propose 'kernel contracts,' a framework for managing divergence between training and inference implementations of AI models that operate at different precision levels. The work formalizes how finite-precision optimizations can produce different outputs at identical weights and provides mathematical bounds on resulting policy drift, with implications for reliable AI deployment.

AINeutralarXiv – CS AI · May 96/10

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A Regime Theory of Controller Class Selection for LLM Action Decisions

Researchers propose a regime theory framework for selecting controller classes in language and vision-language models, determining whether AI systems should answer directly, retrieve evidence, defer to stronger models, or abstain. The work demonstrates that model expressivity doesn't uniformly improve performance in finite samples, and provides a principled method to match controller complexity to data availability across multiple benchmarks.